Business Intelligence and Self-Service Reporting for MS Dynamics AX. Complete Guide

Transcription

1 Business Intelligence and Self-Service Reporting for MS Dynamics AX Complete Guide

2 WHO IS THIS E-BOOK FOR? This e-book is for those with an interest or stake in the provision of management information, analytics, business intelligence, dashboards and self-service reporting, who: Are existing users of MS Dynamics AX or have recently implemented it Are considering implementing Microsoft Dynamics AX Are involved in the Microsoft Dynamics AX ecosystem for example, partners, resellers, Microsoft employees. It examines: Challenges in delivering management information, BI and self-service reporting in an MS Dynamics AX environment (including those points applicable to virtually all core systems and also those specific to AX) The business pains caused by these challenges The different approaches to tackling these challenges including pros and cons for each.

3 It includes: Practical steps to move forward including: How to compare different potential solutions The top eight success criteria to ensure a stellar implementation How to identify and build an ROI case Useful checklist for each stage A glossary of industry terms explained.

4 TABLE OF CONTENTS: i. Introduction 1. The challenge why is reporting and analysis so difficult? What problems does this cause? Solution Options MS AX options 3 rd party solutions Getting it right 71

5 Introduction Our ERP systems do a great job of running the core operations of our businesses reliably, but even their most passionate advocates will admit they are not always great at reporting. Generally, they fall down in three particular respects. First, the range of standard out of the box reports is not great. Second, the associated reporting tools require far more IT resource to be engaged on report writing than management initially imagined. And third, those reports either standard or custom-written must be run against the live database, slowing it down. Pretty soon, what you end up with is an organisation with an expensive bottleneck in building custom-written reports, and an IT system that slows to a crawl as people try to run the reports that do exist. And not long after that, you discover a subterranean world of management-by-spreadsheet, as people build spreadsheets to get around the inadequacies of the reporting system. In short, instead of one version of the truth, you ve suddenly got dozens. // Page 1

6 This is doubly frustrating as the data held in our ERP systems is gold dust. Everything we need to know to make the best possible decisions on pricing, purchasing, sales activity and operational efficiency. We have the data we need, but getting it out in a way that is timely, useful and pain-free is the problem. We had the information, or rather the data. The challenge was accessing and using it. In some areas, we just weren t asking for the information we needed, as we knew it was going to be painful to get David Sturgess, MD, Countax Garden Tractors Why is this the case with a modern ERP system like MS Dynamics AX? What are the problems, the causes behind them, the knock-on business impacts and how do we solve them? In this e-book, we ll examine each of these issues and help you develop the best self-service reporting and business intelligence strategy to use in your AX business. // Page 2

7 CHAPTER 1: The challenge why is reporting and analysis so difficult? When you are running a modern ERP system like MS Dynamics AX, it is perhaps surprising that reporting is such a chore. Why does a swish, shiny system like AX not provide flexible, ad hoc reporting and analysis out of the box? There are a few answers to this question: // Page 3

8 1. It does (kind of) part 1. The reality is that MS Dynamics AX and most other modern ERP systems do provide lots of standard reports out of the box. If you need to produce a cashflow report or a VAT return, for instance, then you can be fairly sure AX is going to do that, really well, as standard. The challenge comes when you want to produce ad hoc reports reports that the software vendors did not predict in advance that you would need. These tend to be a) specific to your business b) consequently, of high business value and c) frequent. An example would be a report on The total margin generated by sales of Product Group A to customers in Poland in Calendar Q1, broken down by sales rep and compared to last year. 2. It does (kind of) part 2. To create new, ad hoc reports you need some technology and tools. Microsoft Dynamics AX does ship with some of these. Your AX package includes SSIS (SQL Server Integration Services), SSAS (SQL Server Analysis Services) and SSRS (SQL Server Reporting Services). // Page 4

9 If you re a tech whizz who knows what to do with these tools, who knows AX really well and who understands your business too, then you can use these tools to create new reports. The downside is that most people are not. If you have these skills in-house then bottlenecks will form around the one or two people who can create new reports. If you do not, you will need to employ or contract someone in. In either case, new reports are slow to create and then need to be maintained. 3. Normalisation Easy, self-service reporting is always impossible over an ERP on its own, because of normalisation. Normalisation is the way in which system architects and programmers design the databases that underpin your ERP system. They don t do it for fun, it is done for good reasons, but it does make reporting really difficult. With a normalised database, information is spread across lots of tables. Imagine, for instance, a table of invoices. Each invoice will have a customer associated with it and that customer will have an address. // Page 5

10 Rather than have the address stored on every invoice, however, we store a customer code (or similar) on the invoice table, then have a separate customer table, keyed by the customer code where the address details are stored. The advantage of this is that if you then want to change the address, you only have to do it in one place. The disadvantage is that if you want a report of all invoiced revenue for Cheshire, then you have to join multiple tables together to make this happen, which is what turns something seemingly simple into a complex, IT person s job. In real life, the complexity is much greater and modern ERP systems are made up of literally hundreds of individual tables. To get almost anything meaningful out of them, you have to join the tables together (using a language called SQL structured query language ) and relatively simple or common business reports may require multiple tables to be joined. To bring this to life, MS Dynamics AX version x.x, for instance, has over 1380 tables with an average of around 105 separate columns in its database (assuming you are running the standard package with no modifications). // Page 6

11 SQL over MS Dynamics. Image credit: mibuso.com 4. Database Performance Running complex queries over databases slows them down. We now know why reporting over an ERP system database is complex. because of normalisation. So when we want to get a meaningful report, we have to build an SQL query that joins multiple tables together. The bad news is that this kind of query negatively affects performance of the database. The best-case scenario is that your report is going to run slowly (the kick-off the report then go for a coffee scenario). // Page 7

12 The next best case is that in order to serve your reports (and keep your system running at the same time), you have to upgrade your hardware (the throw more horsepower at it scenario). The worst-but-not-that-uncommon situation is that when you run certain reports at certain times of day, the performance of the whole system can be affected. This is pretty scary when you consider that AX is also running your sales order entry processes, warehouse, and maybe your production. We have seen at least one customer where they used to send out a tannoy announcement just prior to running certain reports, warning users to get off the system and go for a coffee, while the sales report runs. 5. Not all information is in your ERP Not all the information that you need in your reports is in your ERP. No matter how clever or nifty the ERP system is, it can t really be expected to tell you something it doesn t know. So if you have information that isn t held in the ERP but which you do want to include on a report then you have a problem. Many businesses have ancillary systems that hold valuable data, such as CRM, e-commerce or HR systems. // Page 8

13 Many also have information only held on spreadsheets. Good examples include budgets, targets, rebates and ancillary costs. So while ERP vendors ship their products with the reports that they think you ll probably need every day, inevitably you re going to want many more reports that are specific to your business, your managers and your situation. It s these very ad hoc reports that represent the greatest value to your business. But because of the technical nature of reporting tools and the underlying normalised nature of your ERP system s database, the business user is never going to be able to self-serve their own reports and/or analyses, with the tools that come out of the box. And those technical users who can use these whizzy, complex tools are going to become bottlenecks, and spend their lives creating and maintaining reports for others. // Page 9

14 CHAPTER 2: What problems does this cause? In the previous chapter we learned about why ad hoc reporting and analysis is difficult in MS Dynamics AX. But does this matter? What business problems does not having a BI system cause? // Page 10

15 Spreadsheets replace proper reports to fill the requirement gap for ad hoc reporting, managers create spreadsheets with data downloaded from the ERP system, then manipulate the source data into the required finished result. This is time-consuming and error-prone. And it means that managers are jockeying Excel, rather than doing their day job. Verdict: lots of people with cumbersome, out-ofdate spreadsheets, not doing their proper jobs. Efficiency. At Matillion, we use a phrase, the fictional reporting day. This is a story of a business manager who decides to analyse some aspect of his/her business. They sit down at 9am and by 5pm they ve built a great big spreadsheet. Between 5 and 5.05pm, they actually look at the spreadsheet results and interpret what it says. In other words, they ve actually spent the day manipulating data and only a few minutes performing any analysis. And when they want to look again, or change anything, they have to re-build the spreadsheet. Manually manipulating data, a slow and expensive means to an end. // Page 11

16 Making information-driven decisions. When data is hard, or expensive, or slow to work with, it s sometimes easier to make business decisions based on the best information to hand, rather than the complete picture which is buried in the ERP. Giving a discount on a product that s selling strongly; giving preferential terms to a high-revenue customer who, on closer inspection, is delivering low margins and is a slow payer; buying stock that is sat on the shelf elsewhere in the business. These are all examples (and reasonably common examples) of the sorts of business decisions that can be made without the right information to hand in a timely manner. And often, companies have the data, just not the time or technology to use it in a timely manner. Making decisions without the best information at hand could be (and probably is) costing you thousands. Dispute. When managers create their own management information in Excel, they can sometimes come up with different answers. Ultimately, this means that one of them is wrong (or possibly both). But, perhaps more importantly, it means that rather than discuss the business issue at hand, they will more likely discuss the data discrepancies. My report says 50. Mine says 51. Agreed, but the target was 500, and we should be talking about that. Teams unaligned and debating the wrong thing. // Page 12

17 Risk. The skilled technical or financial employees who know how to create reports become bottlenecks. They also become single points of failure. They are the only people who can create reports so if they re on holiday, poorly or, worse, leave the business permanently, you can be in real trouble. - A big problem, if someone leaves. Drain on IT resource building and maintaining reports can swallow up IT resource. Programmers build reports. Analysts build reports. Ops guys make servers cope with running reports. No one can get on with doing what they want to which is improve the business with better systems. Your IT team is buried under reports. // Page 13

18 Checklist Evaluate your reporting requirement. Does your business need reports that are not provided as standard with MS Dynamics AX, and do new reporting and analysis requirements crop up frequently? Analyse the problem. How much time does your business spend producing Excel spreadsheets? How quickly can you get an answer to a business question that requires a new report or analysis? Are you making decisions without all the data at hand in a timely manner and, if so, how much could that be costing you (in pricing, working capital, lost opportunity and so on)? Locate your data. Is all the data you need in a single instance of MS Dynamics AX, or is it spread across multiple systems, spreadsheets or sites? Identify risk. Are you reliant on key skilled people to extract and process report information for you? Do these people form bottlenecks? What would happen if they became unavailable? Build a business case for a business intelligence solution based on the money you could save/make through better informed decisions and improved situational awareness; the time and resource you would save by not manually creating reports and spreadsheets; the risk mitigation; and the improved agility of removing bottlenecks around a small number of key employees. // Page 14

19 CHAPTER 3: Solution Options So now we understand why MS Dynamics AX and frankly all ERP systems struggle to provide us with fast, easy-touse ad hoc analysis and reporting. We understand, as well, the impact this has on our business in lost opportunity, wasted effort and risk. The good news is that these problems aren t new (even though your MS Dynamics AX implementation might be) and there are various ways you can go to address the challenge. In this chapter, we examine the various solution options. It's worth considering that each option has its pros and cons. One of the biggest differences between the different approaches is how much work you will have to do to implement and maintain the solution. So consider carefully. // Page 15

20 MS AX Options Your MS AX software is built on top of a Microsoft SQL Server relational database. This is one of the underlying technologies that make AX work. SQL server comes with three tools (or utilities) that you can use to help you with reporting: SSRS, SSIS and SSAS. These tools are all great and enterprise-scalable, but they do require pretty extensive skills to use, and inevitably have their own pros and cons. On the positive side, you do have these tools already. Be warned though... often, as soon as you start to use these products, you'll realise you want your reporting done on separate infrastructure (one or more separate servers, which you'll have to license for SQL Server, as well as for Windows and any other software) so you end up not actually using the bundled stuff. Without being unfair to Microsoft, this is a fairly common technique in their licensing model bundle everything in, so you think it's free, but then architecturally ensure you are going to need to buy more to make it work properly. The big cost of using the built-in MS stack is going to be in skills, people and consultants. // Page 16

21 Neither SSRS, SSIS nor SSAS are finished solutions, or anywhere near it. They are quite low-level tools which technicians can then use to build a BI or self-service reporting solution. To use an analogy, with these tools you are not buying a house, you're buying bricks and a trowel. SSRS, SSIS, SSAS Bricks and trowels, not a house As with almost all bespoke software projects, you need to consider carefully the staff and consultancy costs involved the costs involved to get to a live 'version 1, but also those to maintain the software going forward and, usually most expensively, respond to changing business requirements, user requests for new reports, new calculations and any other required modifications. // Page 17

22 On this last point, bear in mind that if you are using the Microsoft stack, then business users are typically not going to be able to create their own new reports. The tools involved are technical, so new reports, analyses, dashboards and cubes are going to need to be created and maintained by IT, incurring costs and potentially causing bottlenecks and delays. The figure above is an extract from our popular infographic exploring the delusions and bottlenecks around Management Reporting. To view the complete infographic click here. // Page 18

23 The acronyms explained what are SSRS, SSIS and SSAS? SSRS SSRS stands for SQL Server Reporting Services. This is the easiest tool in the bundled Microsoft stack to explain. SSRS is simply a report design tool, similar in many ways to something like Crystal Reports. Technical users can use SSRS to design reports, which can be run and printed. There s a good degree of layout control and technical options available. To deploy reports designed with SSRS, in such a way where users can access them themselves, you ll need a compatible Microsoft Sharepoint server (usually as part of an intranet), so if you ve got one of these already, great stuff. If not, you re going to need to run a Sharepoint implementation project before you can deploy SSRS-based reports. Sharepoint will require its own licensing, hardware and deployment effort, and you will also need to consider user security (Active Directory) and training. SSRS reports deployed to a Sharepoint intranet can be accessed directly by business users employing their web browser. // Page 19

24 They can use drop-down boxes and the like to filter/tune reports. Bear in mind, though, that SSRS is not a self-service reporting solution, and so users will not be able to build their own reports, change the shape of reports, or drill down into the underlying data. Authoring of new SSRS-based reports is a technical activity, requiring knowledge of SQL syntax, the underlying table structure of AX (which is complex) and also good accounting/business process/financial knowledge (or the close support of the finance department) to ensure that reports use the correct logic and fields, and reconcile back to the account appropriately. SQL Server Reporting Services (SSRS). Image credit: technet.microsoft.com // Page 20

25 There s also one big heath warning to consider when using SSRS. If you are using SSRS pointed straight at AX, then you are pointing it straight at the operational database that runs your business. Using SSRS (and, in fact, any standalone reporting tool like this), it is easy (and normally essential) to end up creating quite complex underlying SQL queries. These, in turn, can put very high workloads on the SQL server that underpins your AX system. The result is that reports run slowly or potentially very slowly. Far more importantly, however, is that while your SQL server is chugging away, trying to answer the complex queries that SSRS has asked it, then the rest of the database will slow down degrading performance for your whole business. Order entry, warehousing, manufacturing can all be slowed down by someone running a report. The way to avoid this is to run SSRS over a separate database, rather than over the production one that underpins your AX system. You can achieve this by implementing a replicated copy of your AX SQL Server, for which you will need an extra copy of SQL Server (usually 5-12k), an extra physical server and associated operating system/backup software and so on, and some sort of batch or real-time replication software purchasing/configuring. Alternatively, and preferably, you will build a data warehouse. More of which in later sections. // Page 21

26 SSIS SSIS, or SQL Server Integration Services, is another product bundled in with the SQL Server that underpins your Dynamics AX ERP system. SSIS isn t a reporting tool. It is what s known as an ETL (Extract, Transform and Load) tool. A tool for mapping data from one database to another to extract from the source database, transform the data, that is, change it to better suit your needs in the target database, and then load it into the target database (in this context, the database you re going to report over). There are lots of ETL tools available, and SSIS is Microsoft s offering in this space. In the previous section, we looked at one of the reasons why it is a good idea to report over a separate, replicated copy of your AX database for reasons of performance. If you run reports that have complex SQL statements within them, then you risk ending up with slow reports and, more importantly, risk slowing down the production system. There s also another reason why it s a good idea to report over a separate copy of the database. Again, in the previous section we explored why the underlying database of MS Dynamics AX is so complicated because of normalisation. This in turn makes reporting complicated the preserve of skilled IT and finance professionals. // Page 22

27 However, normalisation is not required for a database that is being designed to only support reporting. So if you are going to have a separate copy of your database to support reporting tools, you may as well design it to be denormalised, that is, design it to be simple to report over. The process of simplifying a complex, normalised ERP database (such as that found underpinning AX) into a simpler, optimised for reporting database is called denormalisation. While the standard AX database is normalised and thus has data spread across many different files and columns, a de-normalised database puts all the data onto as small a number of tables as possible. This improves performance and, even more importantly, makes it much simpler to build reports. This separate, simpler, de-normalised copy of your AX database is often called a data warehouse. SSIS is the tool you use to map and pump your data between the source AX database and the target, denormalised data warehouse database. SSIS is an IT person s tool. The skills required are all those required for building a simple SSRS-based report, with some database design, data warehousing and programming skills thrown in. // Page 23

28 MS SQL Server Integration Services, screenshot. Image credit: technet.microsoft.com So if you have the skills in-house and the time /bandwidth /budget, then you can design yourself a de-normalised data warehouse which supports your reporting needs, and then use SSIS to build and deploy ETL (Extract, Transform and Load) jobs which will map the data from your production AX database to your new data warehouse, typically on a scheduled basis (nightly, for example). You can then write reports over the data warehouse using SSRS (see previous section) or in fact, point any other analysis/dashboard/self-service reporting tool at the data warehouse. We ll be covering some more of these in the sections below. // Page 24

29 Be aware that the creation and maintenance of the data warehouse and associated ETLs is the big job in delivering a business intelligence or self-service reporting solution. It is the most important job too, but it is a big job and one that doesn t stop the day you go live with version 1. Changing business requirements and requests for new or modified fields or calculations mean that you never stop looking after the data warehouse and requisite ETL jobs. As such, only embark on an SSIS-based data warehouse project if you have the IT and budgetary firepower to dedicate the resource required to it, in both the short and the long term. A data warehouse and ETL-based solution is the proper way and, we think, the best way of delivering BI/self-service reporting, though. So don t be put off. Using SSIS, another ETL tool or using a solution such as Matillion BI, is, we believe, the only way to deliver self-service reporting, BI and analytics properly. // Page 25

30 How Matillion BI does it Matillion BI is a Cloud-based BI solution designed for MS Dynamics AX users (among others) and it includes a proper de-normalised data warehouse and an ETL layer. The crucial difference, however, is that you don t have to look after the ETL layer. So you get all of the benefits simplified shape of data, one version of the truth, blistering performance but without having to take on the skills or run the complex project required to deploy a tool like SSIS successfully. If you want to find out how we do this, you can arrange a personal demonstration here. // Page 26

31 SSAS SQL Server Analysis Services is the final tool that comes bundled with the underlying SQL Server that you get with MS Dynamics AX. It s what s known as an OLAP engine, which is one of the technologies you can choose to use to deliver drill-down and slice-and-dice style functionality to your users. As with the other Microsoft tools already discussed (SSRS and SSIS), SSAS is a tool to which you add skill and effort to manufacture a finished solution. Also, again like SSRS and SSIS, while SSAS does come bundled with your SQL Server, it s likely that in a production deployment, you would want to install a separate infrastructure to support it, meaning that, in effect, you would be purchasing it twice over (along with the required hardware, operating system and support software). OLAP tools, as with other business intelligence tools (and as opposed to simple reporting tools), enable users to analyse multi-dimensional data interactively from multiple perspectives. OLAP consists of three basic analytical operations: consolidation (roll-up), drill-down, and slicing and dicing. At the core of all OLAP systems, Microsoft SSAS included, are OLAP cubes. Cubes hold your business data in a way // Page 27

32 organised to allow easy, drill-down analysis and consist of numeric facts called measures, which are then categorized by dimensions. A simple example would be a cube that contains a retail store's sales as a measure, and date/time as a dimension. This would, for example, allow the user to drill down through sales by year, into quarter, month, week then day. Extra dimensions could be added for sales assistant and product, meaning the user could answer questions such as, show me the top sales assistant for coats in Q1 of this year. At the core of SSAS, like all OLAP tools, are cubes. To access the cube and its functionality, you need a front-end tool or interface something for the user to use and view the data. // Page 28

33 With other OLAP technologies, such as Cognos (IBM s offering in this space) or Business Objects (from SAP) this front-end tool comes bundled with the product. With Matillion BI, you get a web-browser based interface delivered across the Cloud. With SSAS, you use Microsoft Excel to access the cube, with a pivot table. You can also connect an SSRS report to an SSAS cube. The report can then be deployed out to users though Sharepoint. This is quite illustrative of how Microsoft solutions often work. You absolutely can deliver fantastic reports and analysis functionality out to the user, but to do this you re going to need several technologies, which you then knit together yourself. Design the data warehouse in a new instance of MS SQL Server. Populate the data warehouse with ETL jobs designed and deployed using SSIS. Create multidimensional OLAP cubes over the data warehouse using SSAS. Then build reports over the cubes using SSRS. Finally, deploy the reports to users employing Sharepoint and provide security by integrating in Active Directory. And, optionally, also allow access to the cubes using Excel. Six different technologies are required to deliver the finished solution, all of which (with the exception of Excel) require indepth expertise to deploy and support. Bricks and trowels. // Page 29

34 Using a 3 rd party solution If taking on the Microsoft stack doesn t seem like the right option for you because of the costs involved, or because of your requirement for a faster time-to-benefit with your solution, then there are plenty of other options for you to consider. In this section, we ll take a brief look at each of the other options and the associated pros and cons. There are dozens of reporting, analytics, BI and big data solutions available in the market. For simplicity, we re going to group them into six separate types: 1. Traditional, tier-1 business intelligence systems (Microsoft, Cognos, Business Objects, Microstrategy, Hyperion, for example) 2. Static reporting tools (Crystal Reports, for example) 3. Data visualisation tools (Qlikview, Tableau, for example) 4. Cloud-based tools (Birt, Birst, GoodData, for example) 5. Analytics and data mining software (SAS, SPSS, for example) 6. Business-Intelligence-as-a-Service solutions (Matillion, for example) // Page 30

35 1. Traditional tier-1 business intelligence systems Business Intelligence solutions have been around for quite a long time. This is because the problems explored in earlier sections of providing easy-to-use, performing, self-service reporting over complex normalised data sources have also been around a long time. The database that underpins Microsoft Dynamics AX, MS SQL Server, is what s known as a relational database, or RDBMS (relational database management system). RDBMSs have become the predominant choice for the storage of information in databases used for financial records, manufacturing and logistical information, personnel data, and much more since the 1980s. No sooner did they become popular than a solution was needed to report over and analyse them easily and powerfully. // Page 31

36 While business intelligence and the then-crucial technology of OLAP cubes can trace their heritage (just about) back to the 60 s and 70 s respectively, it was in the 1980 s and 90 s that OLAP-based BI solutions really came to the fore. Essbase (now an Oracle product) was the first major product to market and the OLAP industry experienced strong growth in late 90 s with dozens of commercial products joining the fray. Consolidation of the market left four BI mega-vendors who are: IBM (Cognos) Microsoft SAP (Business Objects/Business Warehouse) Oracle (Hyperion) The consolidated nature of the mega-vendors can be beneficial for large enterprise customers, as it means they have fewer vendors to deal with, which also opens opportunities for licensing deals. But the downside comes from the complexity and interoperability of the products these vendors have acquired into their stacks. We ve already seen, for instance, how you can need up to six Microsoft products to deliver a solid BI experience to the end user and the story is similar (or worse) with the other megavendors. // Page 32

37 Cognos, for instance, is a brand, not a specific product. Its main product, Cognos 8, is actually made up of at least eight different tools (Report Studio, Query Studio, Analysis Studio, Metric Studio, Metric Designer, Event Studio, Framework Manager and PowerPlay Studio). The story is similar with SAP Business Objects/Business Warehouse and also with Oracle Hyperion. To bring the interoperability issue to light, Gartner, the Boston-based, world #1 IT analyst firm, ascribes the lower ratings given in its customer experience surveys for IBM Cognos and SAP Business Objects to the result of postacquisition issues, such as interoperability and ease of deployment of its products. Alongside the mega-vendors, there are still a couple of pureplay traditional vendors left, notably, Microstrategy. These are heavyweight, traditional BI solutions, but owned by independent companies. The pure play vendors are more integrated than their mega-vendor competitors, but are still heavyweight solutions requiring complex implementations. Implementing a tier-1 BI system Successfully implementing a traditional tier-1 BI solution in your business is going to be pretty similar to how you would go about delivering BI using the Microsoft stack (or rather, the same, as Microsoft is one of the tier-1 mega-vendors), as // Page 33

38 covered in the previous sections. In brief, lots of skills, work, manpower and consultancy, both to get to version 1, and to then support the solution on an on-going basis. Microstrategy, for instance, in their own whitepaper (Total Cost of Ownership of Business Intelligence Solutions) describe how the software license cost represents only about 7% of total cost of a business intelligence solution. The biggest single cost is associated with staffing required to implement, run and look after the software. Source, IDC survey of 300 customers covering various tier-1 platforms. Image credit: Microstrategy Microsoft are on record in The Wall Street Journal as saying, A BI project requires a significant number of skilled personnel, which represents the largest cost component over // Page 34

39 the BI application s lifetime the initial purchase is only 5% of the total cost of owning and maintaining a program. According to Gartner again, if you take the three-year cost of ownership of a traditional business intelligence solution, only 8% of the cost is the upfront investment in technology. Source, Gartner. Image credit, Microstrategy. So deploying a tier-1 solution requires deep pockets, a level of competence in IT project delivery, and a reasonably long window of time (we would suggest months). It is, in part, for these reasons that the level of project success implementing traditional BI solutions is so low. Again according to Gartner, up to 70-80% of traditional BI projects fail. With such a high statistic, you perhaps have to question the definition of failure. But nonetheless, this stuff is not for the fainthearted. On the upside, the tier-1 BI vendors do, of course, have some pros. They didn t get to be the biggest just by buying everyone else up. // Page 35

40 With a tier-1 BI system such as Cognos, Hyperion, Business Objects/Business Warehouse or Microstrategy, the main thing that you can rely on is the sort of features that you need to ensure a suitable deployment in a large enterprise. Features such as: Scalability for deployment supporting hundreds or thousands of users Extensive non-functional features to support the complex security, availability, redundancy and audit requirements of large organisations Completeness of vision that is, there s a product, tool or offering for every bit of BI you might ever want. In summary, then, if you re a large organisation with hundreds or thousands of users and extensive non-functional requirements for your strategic BI platform, then a tier-1, traditional solution is a good way to go. You re going to need plenty of time, budget and resource to get the job done right but this is to be expected with a requirement like this. // Page 36

41 // Page 37 Be aware that your strategic BI solution could be complemented/supplemented with tactical, departmental or local BI solutions to provide quicker, more cost-effective and more agile solutions to work alongside the strategic BI platform.

42 2. Static reporting tools Static reporting tools are widespread, often coming bundled in with products for the purpose of authoring new reports. The most popular, and one you will almost certainly have heard of (if not used), is Crystal Reports. We have already discussed another your bundled copy of Microsoft SSRS is a static reporting tool. Static reporting tools are used to author pixel-perfect, printready reports that usually point straight at the underlying source data. A typical Crystal Report. Image credit, crystalreportsbook.com // Page 38

43 These tools are great if you want a cheap way to create a small number of static reports that are not going to change very often (or ever). There are several drawbacks with static reporting tools, however, namely: Authoring new reports is technical. This is partially because the reporting tools themselves are reasonably involved and aimed at power-users or programmers. It is also because a static reporting tool such as Crystal is pointed straight at your normalised, production AX database. As we explained in The Challenge Why is reporting and analysis so difficult? and also in SSRS, this means that you need to understand SQL and the database files, and have a level of financial/business proficiency to produce reports successfully. Partly because of the above, producing reports in Crystal or other static deployment tools is slow and timeconsuming. It might take hours or days to author a new report not including the time spent waiting for the availability of resource to build it. The usual performance problems associated with pointing reporting tools straight at the normalised, production AX database will be present slow reports and a potential slowing down of the core system itself. // Page 39

44 Deployment options are limited or require extra products. Crystal, as standard, requires a viewer tool to be installed on the PC to access its reports. You can, however, pay (significantly) more for the Crystal web server and this will then deploy your static reports via a browser (note: of course you ll also need the associated hardware and infrastructure). The web server doesn t solve the other problems, but it does allow you to serve reports out to a wider audience more easily, including to mobile devices. Non-functional requirements, such as security, availability, performance, scheduling are limited or missing. Because these are not business intelligence tools, there is no functionality for drill-down, roll-up, analysis, slice-anddice, ad hoc reporting, data visualisation or OLAP, for example. To outline these limitations is not to belittle Crystal (or other static reporting tools). These are popular, long-standing products with a valid use-case. Their constraints are simply a symptom of the fact that tools like Crystal are designed to do a certain, limited job to allow technically proficient users to author a limited numbers of reports, usually running over the source database, with a high degree of control as to the look and feel, particularly with regard to printing output. // Page 40

45 It s when you want to go beyond this above use-case that Crystal Reports or its similar products run out of steam. There are some benefits with Crystal Reports: Price. Assuming you only want one or two people to be able to author, produce, and generate reports (then, perhaps, manually them on to others), then Crystal Reports can be acquired very cheaply (a few hundred pounds/dollars per user). The web server (required to make reports accessible via a web browser) is considerably more expensive and licensed per user (approx. 13k/$18.5k for a 20 client license) plus required hardware/infrastructure and so on. SSRS, which is another static reporting tool, is bundled with Microsoft Dynamics AX (although, again, to deploy its reports via a browser, you ll need Sharepoint, as covered in the SSRS section). Print layout. Crystal s heritage is the in the provision of software to design pixel-perfect reports, designed to be printed. As such, Crystal Reports does provide great authoring control (to the technical user) to make sure that what you see on the page is exactly what you expect and fits nicely on your company paper. You can add page numbers, bar codes, graphs and lots of other stuff. Crystal isn t the only tool that does this, but it does do it well. // Page 41

46 Adding reporting to applications. If you develop your own software and want to add reporting (live, application-led, point reporting) into your application then using Crystal Reports Developer Edition or SSRS is an option here. Rather than reinventing your required reporting functionality, you can leverage someone else s, which is usually a good idea. There are other open source packages that can do this for you, too. If you re trying to solve the challenges described in section What problems does this cause?, then a static reporting tool such as SSRS or Crystal Reports is no the solution. But if you simply want to manufacture one or two, print-ready reports, for access by a small number of users and which won t change very often, then (performance considerations aside), this may be a cheap option to consider. // Page 42

47 How Matillion BI does it To tackle the still-present requirement for pixel-perfect, printed reports, Matillion BI ships with its own report authoring tool called ireport. While business users will usually create their own reports, in minutes, using just their web browser and without needing any technical skills, there will be times when, as a business, you do want to spend a little more time getting every font, colour and logo just right and making sure a report looks great when printed in A4 or letter paper size. ireport provides the more advanced user with an authoring environment to accommodate this requirement. The crucial difference is that when you are happy with the report, you simply upload it to Matillion BI, which then serves it up like any other Matillion report via the web browser. Then, because it s in the Matillion BI environment, it benefits from non-functionals such as performance, security, availability and scheduling. The report author using ireport designs against the Matillion data warehouse (rather than over the complex AX database) which makes the report design process much easier than with a traditional static reporting tool like Crystal and also avoids the performance problems. // Page 43

48 3. Data visualisation tools Data visualisation tools are pretty popular right now, and they are awesome at making data look great. Using a data visualisation tool such as Qlikview, Tableau, or Microsoft Excel PowerPivot, the semi-technical user (an IT professional, for example, or a tech-savvy business analyst or a data scientist) can produce fabulous data visualisations and dashboards reasonably easily. Data visualisation tools, as with Crystal Reports, are primarily client-installed software tools that is, you install them on your PC as you would with Excel or Powerpoint. The funky graphics they are capable of creating mean that they need the PC s full processing power, and it s the PC that does most of the work in creating the reports (rather than the powerful server, as would be the case with a tier-1, Cloud or BI-as-a- Service solution). // Page 44

49 Data visualisation tools have two very strong use cases: 1. For the data professional who wants to access lots of different data sets day-to-day, and who has the skills to understand that data and how it is structured, then data visualisation tools such as Tableau, Qlikview and PowerPivot deliver an almost unparalleled ability to access, join together, and present data graphically. You can point the tool directly at a database and then next minute merge in some data from another source someone just ed you (maybe an XML file, some CSV data or a spreadsheet). You then have truly beautiful data visualisation options to make the data look great. 2. As part of an overall BI solution, where a proper data warehouse and ETL layer is already in place (and hence delivering one version of the truth and simplifying the underlying data complexity). A data visualisation tool is an excellent part of the story, delivering a stellar dashboarding capability alongside the data warehouse and self-service reporting software. As regards to cost, data visualisation tools again can work best in the above models. If you have a small number of analysts, data scientists or power-users wanting to visualise data strongly, buying a few seats of Qlikview or Tableau can be a pretty cost-effective way of achieving this. But for a // Page 45

50 roll-out to a wider audience, this can get expensive. Excel PowerPivot of course is free (assuming you have Excel). Data Visualisation in Tableau. Image credit, Tableau.com With most data visualisation tools, you can also buy a web server component to serve up a dashboard you have authored with the PC-installed tool. This means you can deliver great looking interactive dashboards out to your users. But bear in mind that you ll need the (considerably more expensive) licensing to support this, and, of course, the server infrastructure. And these are view-only environments business users cannot author new reports or dashboards themselves via the browser. // Page 46

51 Is data visualisation right for me? Some of the key questions to ask yourself when considering a data visualisation solution are: Do I need to do just data visualisation? Do I need to do just dashboards? Do I need also need to do reporting/analysis/drill-down/slice-and-dice? Sometimes the answer to the above is I just need to do data visualisation. An example of a situation like this might be analysing flow or pressure data from a process manufacturing plant, engine management data, weather data, crime statistics or web traffic. If the answer is I just need dashboards, then you ll most probably be wanting to just deliver situational awareness over a given area of your organisation probably because you ve already got reporting/analysis/drill-down/slice-anddice boxed off with another solution. // Page 47

52 The reason that it s important to ask such questions is that while graphs, charts and dashboards represent the glamorous end of the BI functionality scale, often what people need even more is the ability to create reports and analyses. At Matillion, we re lucky because as a Cloud-based, BI-as-a-Service provider we can see how much time our users spend looking at reports, versus analyses, versus data visualisations. The answer is about 65%, 30%, 5% in respectively. So while a dashboard or data visualisation is the most visually compelling part of BI solution, it is not necessarily going to be the one that i) you use most, ii) you use first or iii) that if you could only have one thing, you d pick at all. Using Matillion clients as an example again, most of our customers will have a handful of carefully crafted, beautiful and functional dashboards that, once they re created, don t change too much. This is an important point to consider at it leads to answer the question, Do I need just a data visualisation tool?, Do I need a data visualisation tool and something else? or Do I need something else entirely? // Page 48

53 Data visualisation and great dashboards Crucial both in your evaluation of data visualisation tools and in your ambitions to deliver great dashboards for your business is the following maxim: great dashboard software does not equal great dashboards. It is perfectly possible to take a top-of-the-range data visualisation, dashboard, or business intelligence product, and use it to deliver a terrible dashboard. Great technology used to deliver a poor dashboard. Image credit: logres.nl To illustrate the point we Googled Qlikview screenshots. Of the images returned on just the first page, the vast majority were very poorly designed. The above screenshot was on the first page. // Page 49

54 This service incident dashboard breaks many rules of best practice dashboard design: pie charts with too many sections, making them unreadable; colours used inconsistently (the blue for instance means five different things on five different charts), which makes you draw misleading associations; no context given to numbers (it could have been given using, for instance, spark lines); 3D and shading effects used poorly; poor axis labelling; and an overall cluttered design. As a tool to give you meaningful, at-a-glance situational awareness of what s going on in your business, this is poorly designed. The point here is not to do a disservice to data visualisation tools. In the right hands, this could have been a great dashboard. Rather, it s to make the point that graphical functionality is not as important as thinking about how to convey information in the best way. In this example, a far better dashboard could have been created in Qlikview, or in Tableau, or for that matter in any other BI tool or just a copy of Excel. As such, one thing to bear in mind is that buying a data visualisation tool does not equal getting good dashboards. And conversely, you don t need a data visualisation tool to get good dashboards. The dashboard functionality in virtually every other category of tool mentioned in this e-book will be sufficient in terms of graphical capability, when combined with good design approach. // Page 50

55 You can learn more about great dashboard design (and how to avoid building poor ones) in another of our free e- books. Download How to Create Compelling Business Dashboards, a free 110 page e-book, from Matillion.com. In the meantime, one great tip is to look at how quantitative information is conveyed in news media. Open any copy of The Financial Times, The Wall Street Journal or most any other reputable publications and you ll find dozens of examples of data visualisation done well (and often only in one colour!). Data Visualisation in the media Image Credit: Financial Times // Page 51

56 Data visualisation tools, in summary, then are great for power-users looking to author fabulous-looking graphs, charts and dashboards. If you re a data scientist, technical user or tech-savvy business analyst dealing with lots of different types of data every day, then a data visualisation tool is also a great option. Finally, if you ve already got your data in one place and simplified (de-normalised) ideally with a data warehouse (taking away the complexity for the business user and providing one version of the truth) then a data visualisation tool makes for an excellent additional tool to either deploy dashboards (when combined with its web server component) or to provide point data visualisations in a graphically rich way. In this last use case, it is worth noting that many other BI solutions (including tier-1, Cloud and BI-as-a-Service solutions) include data visualisation functionality, specifically to satisfy this requirement. While this included data visualisation functionality will not be quite as powerful as that with a dedicated tool, it will follow the 80/20 rule and, as such, often be more than adequate. // Page 52

57 4. Cloud-based tools Cloud refers to the idea of delivering software applications across the internet, and usually refers to software-as-aservice or SaaS models. You pay to use software on a consumption basis, usually hourly or monthly. The basic premise is simple: it s cheaper, and often better, to outsource something you re only going to do once, to someone who is going to do it lots of times and at scale. It s the same principle that means you don t produce your own electricity, or run your own private telephone exchange. The Internet, web browsers and ever-increasing network bandwidth have made this possible in software delivery and it s the way that, in years to come, almost all software will be delivered. It s getting there already. // Page 53

58 This infographic from KPMG shows how the majority of companies surveyed by them are using Cloud technology already in almost every area of their business and how within 18 months it will be the overwhelming majority. Cloud adoption by business area, Source: KPMG/Forbes // Page 54

59 Cloud also usually means some other things too: Lower up-front cost as you re not paying to build the infrastructure Less risk as you don t spend all the money on day one, before you ve had any value Often, better software Cloud by its nature is modern, and the sector just demands slick, easy-to-use but responsive software, just like we ve grown used to in consumer-facing websites and applications Faster time to market as you don t need to set everything up at the beginning. This analysis applies to most areas of Cloud software, not just Cloud BI. On the flip side, Cloud solutions (again, across the industry) may not be as mature as traditional, on-premise solutions. Cloud solutions usually arise in one of two ways: 1. An existing, traditional software company ports a version of its product to the Cloud this usually makes for quite a poor overall solution, particularly in the early days. You often end up with the worst of both worlds compromised functionality and not that much more costeffective cost/cost of ownership. // Page 55

60 2. A new, built-for-the-cloud solution is established, either by an existing software company or a new market entrant. These solutions are the genuine article, and you can normally tell one as soon as you see it. It s just going to look a whole lot more modern. Because it s been designed for the Cloud from the ground up probably taking advantage of concepts like multi-tenancy, infrastructure-as-a-service and modern development frameworks/concepts it s going to deliver the benefits of Cloud in terms of cost, risk and usability. The downside, of course, is that in the early days, because it s brand new, it s probably not going to have all the features of a traditional on-premise solution In the Cloud BI market, you ve really got two main options: Cloud-based front-end BI or dashboard tools, such as Birst, BIME and GoodData Business-Intelligence-as-a-Service solutions, such as Matillion BI. We ll cover BI-as-a-Service in a later section. Cloud-based BI front-end tools like Birst and GoodData are tools. So just like the Microsoft stack, tier-1 tools, Crystal Reports or data visualisation tools, they are a component part of an overall, successful BI solution. Bricks and mortar again. // Page 56

61 Unlike some of those tools, with Cloud-based tools like Birst and GoodData, your infrastructural needs, for the front-end at least, are taken care of. So you re not going to need dedicated servers (or the people, ancillary software or electricity to run them) for the BI front end or possibly for the data warehouse either. What you will still need is the expertise to get data out of the underlying system, design the data warehouse, ETL, and metadata layer, and maintain all this over time. So this isn t a solution option that negates the need for in-house expertise and consultancy or a project to get it all up and running. There is also a new problem that needs to be taken care of how to get your on-premise business data, held in Microsoft Dynamics AX on a server in your offices, out into the Cloud, securely and efficiently. Data needs to be encrypted before it is sent. It should also be transported in a suitable, compressed, framed protocol, otherwise both network bandwidth and latency will constrain the performance of the BI system and its ability to report in a reliable and timely manner. BI-as-a-Service solutions like Matillion BI take care of all this plumbing from source to Cloud, but with a frontend BI tool like Birst or GoodData, you ll need to develop your own strategy here. One use case where Cloud BI front-end tools are really strong is when you want to do BI over other Cloud-based // Page 57

62 tools. Let s say you run Salesforce.com for CRM, Marketo for marketing, Google Analytics for web traffic, Zendesk for Customer Services, and NetSuite as your ERP. These are all Cloud-based products with purpose-built connectors for each of these systems along with the fact that they re already in the Cloud which makes integrating them together in a Cloud BI solution much easier. // Page 58

63 5. Analytics and data mining software The terms business intelligence, analytics, data warehousing, BI, and data mining are often used interchangeably. In the context of this section, data analytics and data mining refer to a specific area of technology. Wikipedia defines data mining as, the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics, and database systems, and data analytics as the discovery and communication of meaningful patterns in data [which] relies on the simultaneous application of statistics, computer programming and operations research to quantify performance. So what does all that mean? Well, there are two lenses through which to answer that question: the how it works lens and the what does it mean for me? lens. To save you reading this whole section, if you want to qualify yourself in/or out now, ask yourself the following questions: // Page 59

64 Do you have very large quantities of transactional information that is, tens or hundreds of millions of rows? Do you have very large sets of data, that is, large numbers of customers and/or products and/or transactions (tens of thousands of each)? Are you in retail, insurance, telecoms, or financial services? If your answers are mostly yes, then you do need to read on. If your answers are mostly no, you can probably skip this bit, or read on anyway. Through the how it works lens, what data mining and analytics is all about is using powerful databases, software and algorithms to gain insight from a data set beyond what looking at the information, slicing and dicing conventionally or reporting over it would do. Statisticians, mathematicians and data scientists use these tools to come up with predictions, scores, groupings and probabilities, which can then be useful to commercial teams within your business. Through the what does it mean for me lens, in the right situations, you can use analytics and data mining tools to make predictions about how, for instance, your customers // Page 60

65 behave. These you can use, in turn, to shape commercial activities such as pricing, offers, product development, packaging and account management. The key players in this market are SPSS (now an IBM Cognos brand product), SAS (the leader in the field), and some open source tools. All the commercial products in this space represent significant investments, and you re going to need a team of skilled statisticians or data scientists to make use of them. If you re a large retail concern, insurance company, bank or mobile phone operator, then this is of course worth it. Some example analytics/data mining use cases : Mobile phone and utilities companies use data mining and analytics to predict churn, the terms they use for when a customer leaves their company to get their phone/gas/broadband from another provider. They collate billing information, customer services interactions, website visits and other metrics to give each customer a probability score, then target offers and incentives to customers whom they perceive to be at a higher risk of churning. Retailers segment customers into Recency, Frequency, Monetary (RFM) groups and target marketing and // Page 61

66 promotions to those different groups. A customer who spends little but often and last did so recently will be handled differently to a customer who spent big but only once, and also some time ago. E-commerce companies use data mining to offer crosssells and up-sells through their websites. One of the most famous of these is, of course, Amazon, who use sophisticated mining techniques to drive their, People who viewed that product, also liked this functionality. Famously, supermarket loyalty card programmes are usually driven mostly, if not solely, by the desire to gather comprehensive data about customers for use in data mining. One notable recent example of this was with the US retailer Target. As part of its data mining programme, the company developed rules to predict if their shoppers were likely to be pregnant. By looking at the contents of their customers shopping baskets, they could spot customers who they thought were likely to be expecting and begin targeting promotions for nappies (diapers), cotton wool and so on. The prediction was so accurate that Target made the news by sending promotional coupons to families who did not yet realise (or who had not yet announced) they were pregnant! You can read the full story here on Forbes. Beyond corporate applications, crime prevention agencies // Page 62

67 use analytics and data mining to spot trends across myriads of data helping with everything from where to deploy police manpower (where is crime most likely to happen and when?), who to search at a border crossing (based on age/type of vehicle, number/age of occupants, border crossing history) and even which intelligence to take seriously in counter-terrorism activities. The technology here, perhaps as it sounds, is pretty weapons grade with a price tag to match. That doesn t make it totally irrelevant to the average Microsoft Dyanamics AX user considering BI, however. Two important take-aways about data mining and analytics: 1. You don t have to do it yourself. There are lots of specialist agencies to whom you can send a data set, on a periodic or one-off basis, who will run a data mining exercise for you. Retailers use agencies like this all the time. Each engagement will typically be quite expensive but will (it is to be hoped) deliver you some commercially useful insight, without you having to maintain a data science/statistics team and expensive data mining software. 2. A big part of the cost and complexity of data mining is in the preparation. Just as with painting a room at home // Page 63

68 once the curtains are taken down, light fittings removed, windows masked off and paintwork cleaned down, the actual painting is pretty quick to do it s the same with data mining. Getting the right data set identified, organised and into the right shape is often a significant chunk of the time/effort involved. A wellimplemented BI or self-service reporting tool helps with this, allowing you to slice and dice the data you need quickly and efficiently, reducing the cost and complexity of the data mining piece, whether you are doing it yourself or outsourcing it. At Matillion, for instance, once a customer is using our BIas-a-Service solution, we already have their data organised and in an environment where we can slice and dice it easily. As such, we re able to offer one-off or periodic data mining services such as basket analysis (who buys what) and RFM analysis in a cost-effective manner. // Page 64

69 5. BI-as-a-Service Business Intelligence as a service solutions like Matillion BI offer end-to-end, grown-up business intelligence and selfservice reporting, with all the different components that we ve so far explored in this e-book (ETL, data warehousing, front-end BI, reporting, data visualisation and so on), tackling all the challenges we ve explored but delivered across the Cloud as one, integrated service. Enterprise-class BI, but easy to use, faster to implement and priced to work for mid-sized organisations (or as a tactical solution in larger companies). // Page 65

70 A solution such as this offers some benefits over the other approaches discussed so far, particularly for companies who don t have large/sophisticated IT functions, for those with time pressures and fast-moving businesses, or for those whose IT department is busy doing other things. Typically, very fast implementation. In the case of Matillion BI, for instance, a typical implementation takes four to eight weeks elapsed, from signed order to users being trained. This would be to deliver a comprehensive BI solution across a significant function of the business (such as an analysis of everything to do with sales). A modern, built for the Cloud user interface. Our user interface is designed very much with ease of use in mind, focussed squarely at business users. As with other Cloud solutions, there are no servers, or software required although with a BI-as-a-Service offering this will apply end-to-end, that is, from your source AX data (and other data sets) all the way through to the user front end (rather than just for the front-end piece, as is usually the case with Birst, GoodData, Bime et al). Even more importantly, no in-house expertise is required. The entire solution is delivered on a turn-key basis, with the BI-as-a-Service supplier eliciting the required business // Page 66

71 rules from you, handling the mapping of source data from AX and any other required sources (such as other systems, or spreadsheets), implementation of any required business rules, design of the data warehouse, and delivery of all this into the finished BI solution. This can usually be done either in concert with the existing IT team, or simply with their knowledge or approval but with no involvement required (freeing them up to do other stuff). This makes BI-as-a-Service a perfect option in instances where IT resources are stretched or unavailable. To be clear, then, there s nothing you can achieve with a BIas-a-Service solution that you can t achieve with a traditional on-premise solution (Microsoft, Cognos, Business Objects et al), or with a hybrid solution using on-premise ETL/data warehouse and a Cloud-based front end like GoodData, Birst or Bime. The difference is that in all of those cases you must: Do a lot of work with consultants or employees or both Run a project Buy multiple components from multiple vendors (both the various software components and also the supporting hardware and ancillary software, like operating systems and databases) Take the risk of the project yourself // Page 67

72 Have the expertise in the relational structure of each of your underlying systems and how to build a working, end-to-end BI solution. This is why BI-as-a-Service solutions, such as Matillion, offer a compelling alternative to many companies who are time-, budget-, or resource-constrained. It offers the same, enterprise-grade design pattern but is delivered without you needing to do work, run a project, buy multiple components, incur risk, or have the requisite expertise. // Page 68

73 Schedule a free demo of BI-as-as-Service software Enterprise class business intelligence and reporting, without the pain. The results? The information you need, without delays and bottlenecks, and a reporting platform that actually works. For the first time you'll be able to: Self-serve to build and access reports Drill-down into business data without technical expertise Get at the management information you need...all without a painful IT project. Schedule time with a Business Intelligence Consultant to chat about your specific needs. Fill out the form, or give us a call at (UK) or MATILLION (US). // Page 69

74 Checklist Now that we ve explored the multitude of different options available, it s time to think about the tool(s) that are right for your business. Use this checklist to evaluate your current systems and identify the reporting requirements of your business. Assess your internal skills capability and budgetary firepower. Can you (and would you prefer to) build your own solution using tools, bricks, and trowels? Or do you need something faster, don t want the risk, or have limited bandwidth to deal with a complex project? Define your reporting requirements and your key, must have features, then compare these against the available solution options. Establish whether one solution would work for you, or whether a hybrid of multiple tools, technologies and skills would provide the best fit to requirements (and be sustainable to implement). Identify your timeline. By when do you need a working BI solution? // Page 70

75 CHAPTER 4: Getting it right Delivering a successful business intelligence implementation can be transformational. Giving business users self-serve reporting empowers faster, more accurate decision-making. Well-designed dashboards and KPIs lead to improved situational awareness and the ability to steer the business with agility. A single version of the truth usually stemming from a well-designed data warehouse reduces conflict, errors, and the invention of management information. Hours of manual work producing Excel spreadsheets can be removed. // Page 71