E-guide BI Analytics Tools Buyer s Guide Part 1

Transcription

1 BI Analytics Tools Buyer s Guide Part 1 Your expert guide to BI analytics s

2 Understanding BI analytics s Understanding BI analytics s and their benefits Rick Sherman, Athena IT Solutions Business intelligence analytics s can leverage data and convert it to actionable information that can benefit organizations. Enterprises are awash in data about their customers, prospects, internal business processes, suppliers, partners and competitors. Often, they can't leverage this flood of data and convert it to actionable information for growing revenue, increasing profitability and efficiently operating the business. Business intelligence (BI) s are the technology that enables business people to transform data into information that will help their business. Although BI s have been around for decades and many consider the industry mature, the BI market is vibrant, constantly innovating and evolving to meet the ever-expanding needs of businesses of all sizes and industries. Over the years, many BI styles have emerged to match the varied ways that business people need to analyze data. An understanding of BI categories and styles is needed in order to match your analytical needs with the appropriate s. Page 1 of 29

3 Understanding BI analytics s Categories of BI analytics s BI analytics s can be grouped into three broad categories that each support various BI styles and capabilities: Guided analysis and reporting. This category includes the traditional BI styles that businesspeople have been using for years to perform recurring analyses of specific data. Examples include a vice president of sales examining the sales pipeline, a marketing manager comparing the performance of various marketing campaigns or a chief financial officer analyzing an enterprise's financial key performance indicators. Years ago, this category was limited to predefined, static reports, but now business users can select, filter, compare, visualize and analyze data using a variety of types. The underlying assumption in this BI category is that the data set and the metrics used will be predefined, but the analysis itself may vary based on the immediate needs of the information consumer when performing that analysis. The IT group or BI team creates most of the BI applications in the guided analysis and reporting category for end users. However, business analysts also produce many BI applications using the self-service BI s discussed in the next section. Regardless of who creates the BI application, IT will be Page 2 of 29

4 Understanding BI analytics s responsible for the underlying data and managing the BI applications used on a recurring basis. The BI styles in this category include: Reports Dashboards and scorecards Corporate performance management Spreadsheet integration BI search Self-service BI and analysis. This category includes the BI s business users use to perform ad hoc analysis of data. This analysis will either be a onetime-only analysis or the formulation of a recurring analysis that will be shared with others. The users of these s have dual roles: information consumer and analytics producer, when they share or publish the BI application they create with the self-service BI. Users of these s typically have the word analyst in their title (e.g., business, financial or human resources analyst). Management staff members may also use these s when they're doing the work of the business Page 3 of 29

5 Understanding BI analytics s analyst (or analytical guru) for their manager or peers, even if their titles might not imply that. Whereas guided discovery s operate with a pre-set collection of data and metrics, the self-service BI s enable business users to add data and define new metrics when performing their analysis without requiring IT intervention. However, there are some considerations to the no IT involvement needed hype that some BI vendors will pitch. First, IT will manage data source access based on need, security and privacy rights, so business users performing their analyses will have to obtain proper privileges to add data sources. Second, the data sources need to be consumable by the BI. Although most data sources can be easily accessed by BI s, there may be specific sources that prohibit access. Third, the data source must be understandable by the business user, which often requires business people working with IT to get an explanation of the schema and definitions of the data they need to analyze. Finally, no matter how easy the BI is perceived to be, having IT help train and support the business in the effective use of these BI s will improve business user's productivity and increase the business return on investment of these s. The BI styles in this category include: Ad-hoc reporting and analysis; Page 4 of 29

6 Understanding BI analytics s Online analytical processing -- also referred to as OLAP cubes; Data discovery; and Data visualization. Advanced analytics encompasses the s data scientists use to create predictive and prescriptive analytical models. This includes predictive analytics, statistical modeling, data mining and big data analytics software. Here, data scientists tend to spend a great deal of time doing data ingestion, integration and cleansing. This category is outside the scope of this article but is mentioned here in order to provide the entire spectrum of BI styles. Here's a look at other BI categories and styles: Page 5 of 29

7 Understanding BI analytics s How to buy BI analytics s Each of the BI styles discussed here originated as standalone, specialized BI s sold by emerging BI vendors. As enterprises recognized their value, the following occurred: The emerging BI vendors with new BI styles grew. The latest BI style was comingled with other BI styles in the products offered by established BI vendors. Larger BI vendors acquired the emerging vendors and incorporated their products into a BI suite offered by the acquiring firm. A key buying question an enterprise must ask is: Is it better to buy a BI suite from one BI vendor or to purchase separate products from multiple vendors? The answer is: It depends. Although other articles in this series will deal with this question in more depth, there are key concepts to consider. First, you need to buy what you need, not just acquire the BI product with the most features because your enterprise may not need all that's offered. The selection process should be guided by business need and best fit. Second, an enterprise needs to examine the cost and skills necessary to develop and manage BI applications, not just purchase or subscription cost. Page 6 of 29

8 Understanding BI analytics s Sometimes, BI suites are more cost- and resource-effective than standalone BI s; however, there other times in which they're much more complex, resulting in higher costs, longer development lead times and the need for a greater pool of skills. Who buys BI analytics s? The investment in and use of BI analytics s has experienced long-term growth, regardless of the economic cycle. It has accelerated in recent years as enterprises are craving data to not just grow and improve, but also to manage their businesses on a daily basis. Historically, BI has been the domain of large enterprises due to complexity, costs and the skills required -- but during the past several years, those factors have changed dramatically, resulting in small and medium-sized businesses (SMBs) becoming significant BI buyers. Many enterprises, regardless of size, initially leverage the reporting capabilities offered by their business application vendors -- such as SAP, Oracle, Microsoft, Infor and Epicor -- by also using spreadsheets to fill in the gaps, especially when their focus is on tactical operational reporting. But this approach often results in data silos, limiting the ability of an enterprise to leverage its BI efforts to grow revenues and operate more effectively. In addition, this approach wastes people's time in comparing and reconciling data from these silos -- time that could be better spent running the business. When the limitations and costs Page 7 of 29

9 Understanding BI analytics s of this approach become apparent, then an enterprise is ready for BI technology that's independent of their operational applications. In the early days of BI, only industries with the most significant need for data used BI; today, enterprises in all industries have information-intensive processes that require BI s. The scale of the information that needs to be analyzed will vary by industry and enterprise size, impacting what specific BI s should be considered; however, that doesn't impact the particular BI categories and styles needed. The BI vendor landscape It can be overwhelming to examine the BI vendor landscape for the first time, as there are currently more than 100 vendors. In addition, the BI market has experienced a significant amount of merger and acquisition activity, so even people in the industry are sometimes confused as to who sells what. BI vendors can be split into three groups: 1. Tech titans. The market leaders by sales are IBM, SAP and Oracle, and they dominate many other technology markets. These companies secured their top positions by acquiring the market leaders about eight years ago -- Cognos, Business Objects and Hyperion. Page 8 of 29

10 Understanding BI analytics s 2. Established BI specialists. Several companies, including MicroStrategy, SAS and Information Builders, have been selling BI s for many years and have an extensive number of users. 3. Emerging BI players. These vendors offer the latest wave of BI innovation, such as data discovery, data visualization and cloud BI. Tableau, QlikTech, TIBCO, Logi Analytics and Birst are some of the vendors breaking out of the pack. Although Microsoft might be considered a tech titan in BI, the company previously wasn't a recognized leader; however, in the past few years, it has emerged as a significant player, particularly in the SMB market. Deploying BI analytics s The two deployment considerations are how the business people will access the BI s (front end) and where the BI application itself will operate (back end). Although there are some BI analytics s that exclusively use desktop client applications, almost all offer a browser-based client interface that works across all major Web browsers. BI vendors were slow to implement native-based mobile interfaces and instead relied on using a browser on a tablet or smartphone; however, with the expanded use of mobile devices for business, that's changing. Page 9 of 29

11 Understanding BI analytics s Although most implementations deploy BI application servers on-premises in an enterprise's data center, more applications are being deployed on private clouds hosted by companies such as Amazon, IBM and Rackspace. When the BI client interface is browser-based, the decision on whether the BI will be deployed on-premises or in the cloud can be made based on an enterprise's data center strategy, rather than by limitations in the BI. There are emerging BI players that are exclusively providing cloud-based BI deployments, often in a multitenant software as a service environment with the cloud BI vendor ensuring security and privacy. Now that you have a better understanding of the different categories, the vendor landscape and how BI analytics s are deployed, the next step is to determine your needs by taking a closer look at some typical use cases for which these s are optimized. Next article Page 10 of 29

12 Understanding BI analytics s determine the Rick Sherman, Athena IT Solutions Before selecting a BI analytics, you should create BI use cases and then match those requirements with BI analytics categories and styles. Over the years, many business intelligence (BI) styles have emerged to match the varied ways that business people need to analyze data across broad product categories that include guided analysis and reporting and self-service BI and analysis. The best practice for selecting a BI analytics is to determine what data your business people are going to analyze and how, so you can provide them with the right kinds of s. The decision of what to buy shouldn't be based on which product has the most features, but rather which product enables the types of analysis your users need and will use. In this article, we'll take a look at how to determine what BI analytics categories and styles are the best match for your business and technical use cases. To support that objective, we will identify the key attributes that define those use cases. Page 11 of 29

13 Understanding BI analytics s BI analytics s: No one-size-fits-all Selecting the for your enterprise could mean the difference between the software becoming an integral part of your business decisionmaking -- or becoming shelfware and the business declaring your BI program a failure. The fundamental mistake many enterprises make is assuming there's one BI product that's right for all; as a result, they base their selection on an extensive features checklist instead of real business needs. Considerations for creating your BI business use cases The key data or analytical characteristics that need to be considered in creating your BI business use cases and then selecting the appropriate BI categories and styles include: Data sources. Will your business people use a predefined set of data, such as from a specific business application or data warehouse, or will they determine what data they need as they proceed with their analysis? Performance measures. Are your company's performance measures, also referred to as key performance indicators or business metrics, already Page 12 of 29

14 defined and accepted or will your business users need to create them on the fly? Understanding BI analytics s Recurring vs. one-time analysis. Do your business people need a recurring snapshot of operational performance on a daily, weekly, monthly or quarterly basis or will the analysis be done just once? Visual analysis. Do your business users prefer tabular reports, basic business graphics such as bar, line and pie charts, or more advanced visualizations such as heat maps, scatter plots and geospatial mapping? Spreadsheet usage. Are spreadsheets widely used for analysis and are they likely to continue to be used in the future? Are the spreadsheets being used to integrate data from various sources or perform sophisticated business rules or advanced calculations? Business knowledge of data. Are your business users familiar with the data, know how different data sources are related to each other and understand data anomalies such as quality issues and data gaps? Business analytical skills. How sophisticated are your business users, analytically? The most sophisticated users will be highly proficient in various analytical techniques and possibly even in statistics, while those on the other end of the spectrum will rely on guided analysis limited to filtering and drill-down functions. Page 13 of 29

15 Understanding BI analytics s Selecting the right BI category and style The following BI use cases are examples that can assist you in selecting the appropriate BI category and style. Many enterprises will have multiple BI use cases, so it's important in those situations to match the right BI category and style to the right business users. Although it may seem that giving every style to every business person is a good thing, the reality is that it will likely overwhelm them and prevent them from using the BI s effectively -- or at all. It's like the story of Goldilocks: The software shouldn't be too hot or too cold, but just right. BI use case: Operational snapshots. The business needs a recurring snapshot of operational performance on a daily, weekly, monthly or quarterly basis. The performance measures and the data that needs to be reviewed are well-defined, and the analysis work typically involves period-over-period performance comparisons or trends. Business people may filter data based on agreed-upon criteria, but they primarily want to quickly do some analysis and then get back to their jobs. To make that feasible, they need tabular reports and easy-to-grasp graphics such as basic bar and sparkline charts. Data consistency is key, with IT integrating data as necessary in the background. Recommended BI category and style: Guided analysis/reporting s BI use case: Limited exploration. Similar to the first use case, the business needs a consistent set of data and performance measures available on a Page 14 of 29

16 Understanding BI analytics s recurring basis, but here the users want to do limited data exploration themselves. They still primarily require a mix of basic business graphics and tabular data, but they also need to be able to drill down into the information for further analysis. That combination can best be accomplished through BI dashboards that are a mash-up of several related graphics with underlying detailed data that users can access, filter and analyze. Dashboards have traditionally been created by IT, but an increasing number of them are now being built by business analysts using data discovery s (more on this later). Recommended BI category and style: Guided analysis/dashboards BI use case: Packaged applications. Corporate performance management (CPM) applications are built to support either specific industries, such as healthcare, or business functions such as finance. The most prevalent applications built into CPM are forecasting, planning and budgeting. CPM applications are often linked to specific enterprise operations systems. Although this is a niche market, if the application matches your enterprise's needs, then there are significant advantages to buying packaged software that incorporates industry best practices into its data and analytical processes. However, the trade-off may be a lack of flexibility matching your enterprise's unique needs. Recommended BI category and style: Guided analysis/corporate performance management Page 15 of 29

17 Understanding BI analytics s BI use case: Spreadsheet integration. Many business people use spreadsheets to gather data from various sources, integrate the data and then create reports. The gathering and integration processes are often timeconsuming, involve many manual processes and require integration techniques that may not be known to most business people. Spreadsheet integration s expand beyond simply importing data in the same manner as CSV or text files by accessing integrated data sources and enabling data blending. In this scenario, business people can continue to use spreadsheets as a BI analytics but rely on the spreadsheet integration s to perform the gathering and integration that was time-consuming and error-prone. Business users often favor this approach because they feel more productive using spreadsheets rather than a different BI for analyzing data. If they're devoted spreadsheet users, it will be difficult to get them to shift -- and, quite frankly, they may be able to do more advanced analysis than various BI analytics s would offer. Recommended BI category and style: Guided analysis/spreadsheet integration BI use case: What data is relevant isn't known prior to analysis. In this use case, not all the data sources or performance measures are predefined and most analysis is done just once. The users are business analysts who are selfsufficient in regards to getting and analyzing data -- they're both data- and analytics-savvy. In fact, they may have created data shadow systems for their business peers and are the subject-matter experts for IT when they're examining data source systems. Data shadow systems are spreadsheets used Page 16 of 29

18 Understanding BI analytics s to gather, integrate and analyze data from various sources. They often grow from a simple spreadsheet used to gather data for a single data source to a complex application involving hundreds of spreadsheets or worksheets pulling data and integrating from a myriad of data sources. BI ad hoc query s were built for business analysts who need to do intensive data exploration to determine what data is relevant to their analysis. Recommended BI category and style: Self-service BI/ad hoc analysis BI use case: Performance measures aren't defined prior to analysis. In this case, there's a known collection of data sources, but performance measures may need to be defined while the analysis is being done. As above, the analysis work may be one-time in nature and typically requires savvy business analysts. However, these analysts aren't proficient in using query-based s -- they're more comfortable with spreadsheets. The best match for them is online analytical process (OLAP) or pivot table analysis s that are just like working in a spreadsheet. Recommended BI category and style: Self-service BI/ OLAP or pivot table analysis BI use case: Not all relevant data sources or performance measures are known. Page 17 of 29

19 Understanding BI analytics s This is another example in which not all the relevant data sources or performance measures are known at the beginning of analytics applications, so business analysts will need to blend in data and define performance measures during the analysis process. In doing so, they may need to engage in extensive data exploration work -- but they typically aren't inclined toward using either an ad hoc query or OLAP-oriented software. They prefer an easy-to-use BI product rather than one with a steep learning curve, which points toward data discovery s. Such s may include data visualization capabilities, but usually include built-in dashboard capabilities that business analysts can use to deliver analysis results to business managers on either a one-time or recurring basis. Recommended BI category and style: Self-service BI/data discovery BI use case: Visual-oriented analytics. In this case, the business analysts need advanced visual analytics capabilities to help them analyze data and present information to others. Advanced visualizations include heat maps, scatter plots, geospatial maps, Gantt charts, histograms and bubble charts. This BI style is typically not sold separately but rather is bundled with other BI styles. If your business people need the guided analysis BI category, then examine dashboard products that have advanced visualizations rather than the basic business graphics. If your business users are looking for the self-service BI category, then data discovery products are your best choice. Recommended BI category and style: Advanced data visualization Page 18 of 29

20 Understanding BI analytics s More than one BI use case Initial BI implementations may only need to support one BI use case, but as BI expands in your enterprise, it's inevitable you will need support for different BI use cases. Although there are BI analytics s that only support one BI category and style, there are BI product suites and data discovery products that will support various combinations of these BI categories and BI styles. Followup articles will examine how to buy BI analytics s and identify what specific BI analytics is best for your company. Next article Page 19 of 29

21 Understanding BI analytics s right BI analytics Rick Sherman, Athena IT Solutions Expert Rick Sherman has advice for organizations trying to settle on BI analytics s: Figure out which features are must-haves, versus nice-to-haves. Selecting the business intelligence analytics that's the best fit for your enterprise is critical to the success of your BI project. This process includes gathering and prioritizing BI requirements, as well as determining use cases and categories and styles. In this article, we will define the key features and functions used to evaluate and select a BI analytics. The criteria can be utilized when it's time to create your request for proposal (RFP). BI analytics selection and evaluation criteria Although industry analyst product reviews can be a good source of introductory research, particularly if you aren't familiar with the overall market, these reviews Page 20 of 29

22 Understanding BI analytics s are often oriented toward selecting the product with the most features. Your organization should instead select the BI analytics that's the best fit for its use cases, meets its budget and can be implemented given its resources and skills. To simplify the process, you may wish to classify the features and functions to consider as must-haves, nice-to-haves and will-not-use: Must-haves. This classification should be unambiguous. In other words, if the product doesn't have this particular feature, it's eliminated from further consideration. Nice-to-haves. Although nice-to-have features aren't required, they're often the differentiators in selecting a product. Will-not-use. Many BI analytics products have a laundry list of features that your company may never use. In that case, don't waste time examining those aspects of products during the evaluation process. Caveat: Although a product may have the features that meet your criteria, there may be special considerations for how those features are obtained. For example, in order for a BI analytics to provide these features, are any of the following required? 1. Custom coding. 2. The purchase of an add-on product from a third party. Page 21 of 29

23 Understanding BI analytics s 3. A specific product edition, such as an enterprise versus a basic edition. These conditions all mean additional time and expense. To ensure an objective evaluation and avoid surprises if this product is selected, you need to determine how to identify and factor the additional time and cost into product comparisons. Overall BI features: The must-haves The following are often must-have features for organizations: Data sources. Access to various databases and file types such as commaseparated values file, text, Excel and XML are basic staples of all BI products. Increasingly, BI analytics s are providing access to specific applications such as Salesforce or NoSQL databases. Your specific needs will determine if these features are must-haves. Data filters and drill-down. The product should enable the contents in a tabular report or visualization to be filtered by data values. Filtering is provided by features such as pull-down lists, search filters and slicers. The product should also allow the user to drill-down from summarized to more detailed data and then drill up (i.e., go back to where they started); this is essential in both tabular reports and visualizations. Page 22 of 29

24 Understanding BI analytics s Web-based client user interface. The product's client user interface for the BI consumer-role should be Web-based. This has become an industry best practice, as it's more cost- and resource-effective for administration, support and deployment than desktop-based interfaces. It's a nice-to-have feature if the BI application creator and administrator roles are also Web-based versus a desktop-based client application. Independent and interconnected mash-ups. When the BI style enables multiple visualizations, including tabular reports, to be displayed on a single screen, the software should allow for these visualizations to be either independent of each other or interconnected. If they're interconnected, data filters and selection affect all visualizations; for example, if a particular attribute is selected, all visualizations share that attribute. Visualizations. The BI analytics must provide bar, line, pie, area and radar chart types, as well as the ability to mix and match various combinations. Security. All BI products must require both user and user role-based security, designating who can create, modify, publish, use and administer the BI applications. You may require the BI product to integrate with operating system or other pre-existing security applications. BI security often involves using the product's security along with a combination of mechanisms from operating systems, networks, databases and the source system. Page 23 of 29

25 Understanding BI analytics s Microsoft Office Data Exchange. The product must be able to import and export data with Microsoft Office products, especially Microsoft Excel. Print and export. The product must allow for print visualizations and tabular reports to be exported to PDF or other graphics. Tabular reports need to be exportable to text files at a minimum and, preferably, to spreadsheets. Must-have features specific to self-service BI use cases There are several must-have features that are specific to self-service BI use cases. These are unique because they provide more data management functionality for the business person creating an analytical application than for an information consumer who is relying on pre-built BI applications with pre-built integrated data. These features include: Select data for analysis. The BI analytics must enable the user to select the data used in analysis and present it as a pivot table-style interface where dimension attributes are placed in rows and columns, measures are selected and filters are applied. Data blending. The product must permit the user to blend data from various data sources. This includes accessing the data and mapping or creating relationships with data from multiple sources. Page 24 of 29

26 Understanding BI analytics s Create measures. The product must enable the user to create and save measures or calculations for use in analysis. These are also referred to as performance measures or key performance indicators. Create hierarchies. The product must allow the user to create dimensional hierarchies, such as by geography or product, to group and summarize data. This establishes the drill-down paths. Save queries and analysis. The product should enable the BI user to save the data filters, selections and drill-down paths used in an analysis so they can be reused. Overall BI features: The nice-to-haves These features often are the criteria that become the differentiators in selecting BI products: Create and publish by business users. The product enables the user to save and share his or her analysis with other BI consumers. Context-based filters. Filters will list only choices that have values given the current selection of facts and dimensions. Context-based visualizations. Only visualizations or chart types that are relevant to the data selected will be listed as options. Page 25 of 29

27 Understanding BI analytics s Advanced visualizations. More advanced visualizations include heat maps, scatterplots, bubble charts, histograms, geospatial mapping and combinations of each of these, such as bubbles on a map. The best mapping capabilities will leverage city, state and country attributes in your data, rather than force the inclusion of longitude and latitude. Collaboration and social interaction: The BI analytics enables a business community that can share and discuss their analysis. This would include annotating analysis to share observations and social media enabling discussion threads or chats. Storyboarding: Business analysis often involves a process or workflow of analyzing different data from different perspectives. Storyboarding enables a series of reports or visualizations to be tied together in a workflow that can be shared. Microsoft Office real-time integration. Beyond simple import and export, the product should provide real-time integration with Microsoft Office products, which enables business people to embed analytics from the BI analytics into a PowerPoint or Excel presentation, for example, and refresh it automatically as the data is updated. Mobile version. The BI analytics should be able to differentiate between viewing BI applications on a Web browser on a mobile device versus a mobile BI application. Page 26 of 29

28 Understanding BI analytics s In-memory analytics. The product should pull data into an in-memory or locally cached data store. In-memory columnar is an increasingly popular feature enabling very fast analytics once the data is loaded. Offline updates. The BI analytics, when it stores its own copy of the source data in an OLAP cube or in-memory columnar data store, should allow users to schedule automatic data updates. Performance monitoring. BI products that monitor report and data usage enable a BI group to improve analytical performance for the business, eliminating bottlenecks and assessing infrastructure needs. BI platform administration. Although all BI s should provide code and version management, there are many application development features, such as team development and user administration, that are useful for larger BI deployments. Other considerations Establishing the scope of your BI project in terms of how many people will use it and what data will need to accessed is the foundation for creating the selection criteria. Monetary considerations such as the anticipated budgets for the initial project, sustaining the BI program and expansion the following year also are key factors in selection criteria. Although you wouldn't go to an architect and just ask Page 27 of 29

29 Understanding BI analytics s to design a house without talking about the size, type of rooms and budget, too many BI evaluation projects have started without any scoping or budgetary boundaries, resulting in time wasted in examining BI products that don't fit their need or budget. The following are often included in evaluation criteria, but since they're very subjective, it's important to provide clear definitions of what the comparison will be based on: Ease of analytical use. There should be different criteria defined for each type of user: information consumer, business analyst and IT. Ease of creating BI applications. There should be different criteria for each type of analytics creator: business analysts and IT. Speed of access. Query performance will vary based on the complexity of queries and amount of data involved. Dashboards with multiple visualizations will need to get query results from many queries. The best practice is to create several pre-built query scenarios and compare how each product performs on these specific examples. The worse practice is to just have evaluators arbitrarily rate the speed. Scalability. The best practice is to establish a testing environment to determine scalability in terms of both the number of concurrent users and data metrics such as volumes, variety and veracity. Page 28 of 29

30 Understanding BI analytics s Platform. Do you prefer on premises versus cloud, open source versus commercial software, operating systems or other infrastructure options? Training. There should be separate criteria for BI user versus administration training. Training may include in-person classes, online classes (live or prerecorded) or Web recordings for specific features or processes. Documentation. There should be separate criteria for BI user online help, versus technical documentation. Once you've created your evaluation criteria, it's time to select a shortlist of product candidates and proceed with your RFP process. To help you create a candidate pool from which to choose, the final article in this series will examine the leading BI analytics s on the market. About the author Rick Sherman is the founder of Athena IT Solutions, a consulting firm based in Maynard, Mass. He has more than 25 years of business intelligence and data warehousing experience, and has worked on more than 50 data warehouse and data mart implementations across many industry groups, sourcing data from a variety of business applications. Sherman's book, Business Intelligence Guidebook: From Data Integration to Analytics was published in He can be found blogging at The Data Doghouse, or can be reached at rsherman@athena-solutions.com. Page 29 of 29