Making Smarter Decisions for Data Discovery Solutions: Evaluating 3 Options

Transcription

1 Making Smarter Decisions for Data Discovery Solutions: Evaluating 3 Options WHITE PAPER The business intelligence market is undergoing dramatic change. New technology, more demanding business requirements and increased disconnect between what users want and what IT has delivered are shaking the foundations of the BI industry. While BI has done great things for some organizations, it has yet to transform business decision-making for a variety of reasons, including high complexity, rigidity of content, long deployment cycles, significant financial costs and disappointing adoption rates that have impacted return on investment. But the single biggest cause of traditional BI s challenges undoubtedly is its foundation in an IT-centric model, rather than in one driven by and for business users. It is this disconnect between what business users need and demand and what IT has delivered with traditional BI that has led to the next phase of BI, called data discovery. Popularized by research firm Gartner and now widely adopted throughout the A TECHTARGET WHITE PAPER

2 Making Smarter Decisions for Data Discovery Solutions: Evaluating 3 Options industry, the term refers to user-driven business discovery that combines technology tools, processes and a business focus on surfacing insights faster, easier and less expensively than traditional BI. This paper seeks to shed some light on the customer pain points that data discovery may address, as well as the necessary features and functionality buyers should look for in solutions. Finally, we ll look under the covers of popular data discovery tools from three leading suppliers SAP, Tableau and Qlik and present some thoughts that should help you make smarter decisions on which tool may be right for your organization. Customer Pain Points Traditional BI has had to work collaboratively with data discovery tools as organizations analytics requirements have evolved dramatically in recent years. While the seeds for change in the BI segment were planted quite a while ago in enterprises across all industries, they have taken on deeper importance because of the business implications of these pain points. These challenges include: Users are struggling to get the information they need, when they need it, to make decisions. Today, business people insist on being able to get their information immediately so they can use it now. A lot of essential data now sits outside the corporate data warehouse and new sources are constantly being added while existing ones often morph into different formats. IT budgets are being stretched to the breaking point, impacting IT s ability to do strategic projects like big data, mobility, the Internet of Things. Business users know the importance of data, but don t always necessarily understand it. So many business users are anxious, impatient and demanding, but too often may have to deal with misleading data and risk drawing erroneous conclusions. Sustained explosion of data volumes and new data types, especially unstructured data which is now widely acknowledged to constitute more than 80% of all data. New market dynamics that are changing the rules of business such as mobility, cloud computing, global e-commerce, Web 3.0 and other transformative technologies. Mapping the Ideal Solution One of the challenges in designing and deploying the ideal data discovery solution is that it really needs a platform that delivers multiple levels of functionality. Only in this way can it enable both IT and business users to derive tangible value quickly and cost efficiently in a manner traditional BI solutions never could. Your comprehensive data discovery solution should deliver the following range of features and functionality: Enterprise governance. Policies that are well established for IT control, but also flexible enough to support diverse users needs, must be supported by the solution to address such crucial governance issues as security, service-level agreements, licensing and ensuring performance at scale. Data and workflow management. Data discovery solutions must ensure full data transparency in order to help business stakeholders profile data that is becoming increasingly diverse. The ability to combine information from different data sources easily and quickly is an essential requirement for data discovery platforms, as well as robust, integrated ETL capability, open APIs and maintaining data integrity after multi-source integration. Application capability. Search, mobility, collaboration and self-service are some of the most essential requirements in an ever-evolving data discovery feature set. Web- and mobile-based application delivery, data visualization, navigation, alerts, dynamic calculations and support for PG. 2

3 WHITE PAPER a range of user-controlled variables should be integral elements of your solution. Performance, including big data scenarios. Analytics, especially including big data workloads such as Hadoop, can tax the performance of many data discovery tools. Adding to the performance complexity is the real-world environment of data access and user discovery, such as virtualized infrastructure, cloud computing and, especially, mobile platforms. Be sure your data discovery solution has accounted for usage in a world beyond traditional onpremises environments. Development. Agile development tools, DevOps and rapid prototyping require greater collaboration between IT developers and business users to ensure that solutions actually address business needs and are flexible enough to evolve over time. Data discovery tools need to allow for such development factors as growing information density that impacts how data is presented (especially for mobile platforms), making demo/starter applications available to speed the development cycle and providing robust APIs for application extensibility over time. Three Options for Data Discovery Solutions Three suppliers of data discovery solutions that many organizations have widely evaluated are SAP, Tableau and Qlik. Each has its own strengths and positions its solution in unique ways, and all three suppliers are well regarded both as companies generally and for their data discovery tools specifically. SAP SAP has the largest share of the BI market, although its market share comes primarily from traditional BI. Its traditional strengths are in large enterprises, many of which have used the company s flagship applications especially Enterprise Resource Planning for years. SAP is a financially solid, well-resourced organization with strong brand recognition, and has traditionally built deep and long-standing relationships in the IT community. SAP s core BI platform is BusinessObjects, but the company set out to broaden its portfolio into self-service by introducing Lumira, which SAP positions primarily as a data visualization platform. In fact, SAP calls Lumira a software solution that helps customers visualize and make sense of their data self-service data visualization for everyone. There are four offerings of Lumira. Lumira Desktop is used for authoring content and was released in Since that time, SAP has launched the Lumira Cloud platform; Lumira Server as a free add-on for HANA for on premise sharing of content; and earlier this year they released Lumira Edge, which is an SMB version of the Server that can be deployed without Hana. According to SAP, Lumira Desktop Standard Edition supports such functions as visual data navigation; transforming and manipulating data; use of Excel and CSV data sources; database server connectivity; sharing datasets with BusinessObjects Explorer; and live data analytics using SAP HANA. The Standard Edition, however, doesn t support integration with BusinessObjects. SAP Lumira Enterprise is required to integrate with the core BusinessObjects platform including universes, and version dependencies exist. Tableau In the BI and data discovery world, Tableau has been synonymous with data visualization. Although much smaller than SAP and other competitors in the data discovery space, Tableau has carved out a strong position in the visualization niche with a core product offering that is considered easy to both deploy and use by business professionals. Like SAP Lumira, the Tableau visualization solution is available in three formats: Tableau Desktop, Server and Online. The desktop version offers fast access for either live or in-memory data analysis, accessing and blending different data sources. The server version is a browser- and mobile-based platform that allows dashboards created in Desktop to be shared among users, and allows for publishing of shared data connections from Desktop. Tableau Online is a hosted, SaaS-based version of Tableau Server and includes such features as cloud-based data connections, mobile support and subscription-based delivery of information to local s. PG. 3

4 Making Smarter Decisions for Data Discovery Solutions: Evaluating 3 Options The company recently introduced its latest version, Tableau 9.0. Compared with earlier versions, Tableau 9.0 is seen as a good step forward with upgraded capabilities across the product feature set. Tableau generally gets high marks for its visualization capabilities, making it a logical upgrade for power users of Excel who want to produce and distribute data visualizations. Users also have the ability to build their own dashboards based on broad applications defined by IT, which provides IT organizations with the enterprise level of control they need, such as security, information governance, compliance, servicelevel management and scalability. Qlik s self-service functionality is ideally suited for business users who like to interrogate the data and explore associations. Creating visualizations is easy to learn, enabling fast time to value. Qlik Qlik offers self-service and guided solutions for data discovery, both built on a core platform engine that leverages an inmemory associative indexing engine. With the introduction of Qlik Sense, Qlik has moved from being a one-product company for guided data discovery (QlikView), to offering an analytical platform with broader applicability. The platform supports guided analytics and interactive dashboards, as well as visualization, self-service and mobile scenarios. In addition, the Qlik platform utilizes an API-centric approach for embedded/web application scenarios. This is a key part of Qlik s value proposition for customers: There are different options within the same technical platform, as opposed to having two different platforms. The Qlik platform allows customers to create sophisticated, user-driven visualizations across multiple, complex data sources and consolidate the information into a single application. What sets Qlik apart from other data discovery tools is the level of interactivity users have with data. All data discovery tools offer some filtering or drill-down on a few aspects of data. Qlik breaks the mold here. Searching across all data resident in all data sources, while interacting with dynamic applications, dashboards and analytics engines on-premises and via mobile devices Qlik helps users uncover hidden trends, ask questions and use a self-service model that empowers business users without taxing precious IT resources. Qlik offers a shared-object library with pre-built data, expressions and visualizations to deliver consistent presentation of data and values. One of Qlik s most attractive qualities is its ability to offer the best of both worlds: IT governance and end-user flexibility. Users can create their own visualizations based on the library of predefined content, or they can create something completely new using that data that has yet to be incorporated. Evaluating the Suppliers and Their Solutions Although SAP, Tableau and Qlik each offer solid solutions in the data discovery market sector, there are tradeoffs and important considerations IT decision makers should be aware of when evaluating these vendors products. While each organization s needs, priorities and challenges are unique, there are some things about these products that evaluators need to keep in mind when determining the best solution for a governed data discovery requirement. For example, consider Tableau. As discussed previously in this paper, Tableau s strength is in data visualization. However, that tight focus also has an important flip side: Tableau is not as highly regarded for exploration, dashboards or governance. For instance, Tableau talks about using Visual SQL to translate drop-and-drag into queries. However, the Tableau visualization product lacks multi-pass SQL, which is a common requirement for calculations and aggregation. This impacts performance and may require modifications of the customer s data warehouse. PG. 4

5 WHITE PAPER Data integration is undoubtedly an important consideration for data discovery solutions, and Tableau has some challenges in this area. For instance, enterprise buyers are likely to encounter limitations working with Tableau in areas such as the number of heterogeneous data sources supported, type of joins, inability to concatenate data sets, asymmetric data blending (data loss) and more. Evaluating SAP Lumira surfaces issues, as it carries with it increased complexity, cost and IT administrative burden. Getting the most performance and functionality out of Lumira typically requires using it in tight alignment with SAP HANA, which adds cost, complexity and deployment time for Lumira customers. Lumira often runs into various limitations, such as data cleansing, enterprise scalability, data enhancements, data integration and associative highlighting. business users, Qlik offers a platform approach with decided competitive benefits. For customers prioritizing data visualizations, the Qlik platform offers a superior experience to SAP Lumira because of its inclusion of smart search and visualizations leveraging Qlik s patented Associative Data Indexing engine. Qlik also offers the advantage of being able to author and access visualizations on any device, with the information display optimized for that device. SAP Lumira offers exploration on a single chart or light filtering on stories with multiple charts; creation of reports may require significant support from the IT organization. Qlik, by comparison, delivers analytics in much less time without any need to predefine aggregates or drill paths. Customers looking to combine data using multiple data sources may run into challenges with Lumira. For instance, when using the merge function to blend data in Lumira, the data needs to be relatively simple; as a result, it can be easy to lose track of what has been included and joined. Using Lumira to query data live from Hana turns off many of the desired data discovery capabilities like data source blending and manipulation of measures. One of the most significant issues IT organizations need to consider with SAP Lumira is that users requiring more data discovery functionality beyond visualization will require additional SAP products to match the capabilities of the Qlik platform. That certainly impacts customers total cost of ownership and makes management more of a challenge. Overall, when compared with SAP Lumira, the Qlik platform offers a number of benefits: Of course, one of the most significant issues that those evaluating Lumira will run into is the need to purchase, deploy and support additional SAP products to get a fully functional data discovery solution combining Lumira s visualization features with SAP s core BI/data warehousing. Deploying SAP HANA and/ or BusinessObjects in concert with Lumira may work for some customers, but it will most likely come at a financial and IT management cost. How Qlik Stacks Up with Tableau and SAP Lumira For organizations seeking a different solutions approach one that combines the enterprise governance required by IT departments with the ease of use and self service needed by Support for all data, regardless of where it lives. Qlik is also built on an architecture that makes it easy for users to blend data without running into the typical traps/rules of traditional SQL/OLAP. Flexibility for the user, such as broader exploration capabilities for data exploration and visualization (robust and mature product rather than new/developing platform). Lower total cost of ownership and more rapid time to delivery. Qlik offers governance without having to purchase, upgrade or deploy other tools (stack independence). PG. 5

6 Making Smarter Decisions for Data Discovery Solutions: Evaluating 3 Options Looking at Qlik compared with Tableau 9.0 in the area of visual analytics, Qlik holds advantages in a number of essential areas. These include Qlik s innovative visualization capabilities ( smart visualizations ), the number of data sources and volumes supported; ability to handle complex calculations across data sets; and a higher level of interaction. Qlik also allows users to visualize and analyze larger amounts of data, not just a small slice of data on visualization. Performance is another key area of differentiation between Tableau and Qlik. Tableau 9.0 remains a query tool, whereas Qlik s pioneering role in the development of in-memory technology gives it a decided edge in performance and power. Additionally, Tableau still has work to do in order to fill gaps in its functionality relating to data transformation and data integration; for typical data discovery use cases, users still have to consolidate and prepare data for Tableau or rely on additional tools such as ETL. Enterprise capabilities such as governance and manageability, story-telling and mobility support all are additional areas where Qlik s long heritage provides it an edge over Tableau. Qlik offers a platform that provides centralized management and governance of all resources, including data, analytics and users. A streamlined management console and governed libraries of content make Qlik a stronger solution for enterprise scenarios. In data integration and federation scenarios, Tableau requires a database management system in order to join data across heterogeneous databases and/or tables. Additionally, links between sources need to be defined at the visualization level there is no ability to publish pre-defined libraries of dimensions and metrics coming from multiple heterogeneous data sources. Qlik allows for federation of any number of data sources in order to provide a richer, cross-functional business analysis, ensuring consistency and re-use. Once the library of dimensions and metrics is defined, Qlik Sense offers real self-service for users, anytime, anywhere, allowing them to create visualizations, dashboards and stories on the same trusted data on the server/mobile, not just visualizations like in Tableau. Even in scenarios where customers are evaluating Tableau primarily as a visualization engine, Qlik offers a number of advantages. For instance, Qlik Sense has very smart defaults and palettes that enable users to create attractive visualizations, maps and dashboards extremely quickly. Users also can easily share visualizations by or on Qlik Sense Cloud by using Qlik Sense Desktop, a free application. Qlik Sense also was designed with a strong eye toward mobility, where Tableau s data visualizations are adapted to unique screen sizes, orientations and native gestures. Finally, Qlik Sense offers a broader array of APIs that allow for easy customization and component reuse and the capability to easily merge BI into web-applications. It s important to re-emphasize that Qlik s approach to data discovery is based on the premise that a single platform rather than multiple, disparate products provides the highest possible value to the customer. By supporting a full spectrum of business intelligence and analytics use cases on a unified platform design with a governed framework, Qlik is best able to support organizations long-term growth requirements as their circumstances evolve and their needs expand. Conclusion Data discovery particularly governed data discovery is the new face of business intelligence. It combines the ease of use, powerful graphical representations and self service desired by business users with the enterprise features and control required by IT organizations. Today s data discovery solutions help organizations make better decisions faster and with greater collaboration among business stakeholders and their IT counterparts. Preferably, data discovery tools help organizations realize fast time to value from their investments through faster deployment and quicker onboarding of business users. PG. 6

7 WHITE PAPER As governed data discovery increasingly becomes an essential part of enterprise decision-making and a way to leverage rather than be overwhelmed by the mounting array and volume of data, making the right decision on a data discovery solution becomes more important than ever. This can be very tricky when trying to sort through potentially dozens of different suppliers and their products, ranging from traditional BI solutions dependent upon complicated and expensive infrastructure stacks to more agile, business-driven solutions. Solutions from suppliers such as SAP and Tableau often will be in the consideration set for enterprise buyers SAP likely due to its long-standing strength with enterprise IT organizations and Tableau usually because its visualization solution is easy to implement and use. But each of those solutions also come with significant limitations or challenging issues which may require either an extensive IT footprint or the utilization of additional tools for a full data discovery solution. By contrast, Qlik offers solutions within a platform that meet the traditional control, security, performance and scalability requirements of an enterprise BI solution, but that also provide the intuitiveness, striking visualizations and ease of use necessary for business users. Buyers looking for a flexible, configurable solution for governed data discovery should seriously evaluate the Qlik platform QlikView and Qlik Sense for their current and longer-term needs. PG. 7