Data Discovery in the Enterprise

Transcription

1 Data Discovery in the Enterprise Five Questions to Ask Before Choosing a Solution A White Paper WebFOCUS iway Software Omni

2 Table of Contents 1 Introduction 2 Can You Empower All Decision-Makers, Not Just a Select Few? 2 Provide Everyone With Appropriate Functionality 3 Check Scalability 3 Don t Ignore Real-Time Operational Needs 4 Are Rogue Dashboards Creating More Questions Than Answers? 5 How Do We Ensure Data Integrity and Prevent Flawed Insights? 6 What Costs Are Associated With In-Memory Limitations? 8 Can You Add Advanced Analytic Capabilities With Ease? 10 What It Takes: A Fast and Flexible BI and Analytics Platform 11 Self-Service Analytics for Everyone 12 Centralized Management and Security 12 Big Data Analytics Performance 12 Scalability 12 Built-In Data Quality 13 Robust Data Visualization Capabilities 13 BI Portal 13 Tools and Apps 14 Conclusion

3 Introduction The business intelligence (BI) and analytics market continues to evolve rapidly under the influence of big data. With increased volumes of structured and unstructured data and a growing demand for fact-based decisions, organizations are seeking new ways to leverage their information. A new crop of data discovery and visualization tools has emerged to address this need. Visualization makes information easier to interpret, understand, and retain. When raw data is depicted through pictures, images, and graphics, it becomes much easier to recognize patterns, dependencies, anomalies, and more. Unlike many traditional BI solutions, which can be slow, antiquated, and complex, data discovery tools promise to free business users from IT reliance. But before rushing to purchase a standalone data discovery solution, consider this: Even though they may seem exciting and novel, data discovery tools only address the information needs of a limited number of users, and in some instances, may actually do more harm than good. The Data Warehouse Institute s Stephen Swoyer claims that users of data discovery tools will consume unvetted, inconsistent, or faulty information, or worse yet use this (faulty) information to generate analytic insights. The latter scenario could compromise the analytic insights that directors, analysts, and managers use to enrich (or in some cases to drive) decision-making activities. 1 This white paper explores what it means to visualize responsibly by addressing five key questions you should ask to avoid the pitfalls and limitations of most data discovery tools: 1 Can you empower all decision-makers, not just a select few? 2 Are rogue dashboards creating more questions than answers? 3 How do you ensure data integrity and prevent flawed insights? 4 What costs are associated with in-memory limitations? 5 Can you add advanced analytical capabilities with ease? By making visualization part of a fast and flexible BI platform, organizations can go beyond the limited capabilities and data quality issues of a niche solution, and serve the diverse information needs of enterprise users, partners, suppliers, and customers. We ll outline the criteria for data visualization success and provide key features of the technology required to achieve it. Case studies throughout demonstrate how leading organizations are leveraging self-service analytics to help everyone make better, fact-based decisions. 1 Swoyer, Stephen. Are Enterprises Getting Serious About Data Governance? TDWI, November Information Builders

4 1 Can You Empower All Decision-Makers, Not Just a Select Few? If your goal is to maximize the ROI from enterprise information by enabling more people to benefit from it, then typical data discovery tools may not be the right approach. Those tools have limited usability, don t scale easily, and can t satisfy operational demands for real-time information. Customer Success Snapshot: U.S. Bank The Organization U.S. Bank is the fifth-largest commercial bank in the U.S., with $282 billion in assets. The Challenge U.S. Bank needed a powerful and scalable BI platform that could make information readily available to more than one million users. Enable small-business clients to view their debit, Visa, and MasterCard transaction data online and run aggregate reports to track corporate spending. The Solution ScoreBoard, a WebFOCUS-based Software-as-a-Service application, allows small business owners and authorized officers to monitor their company s credit card spending over various time periods, and compare payment data with peer companies to discern industry trends. The Result U.S. Bank has improved the online experience for its small business clients, and encouraged more customers to use the Internet channel. Provide Everyone With Appropriate Functionality Current data discovery tools may hinder BI adoption because they satisfy only a small percentage of the user base. Although they allow some more advanced users like analysts to perform deep data analysis, they can be too difficult for the typical business user or, even more worrisome too easy for them to get wrong. Professional analysts will always want advanced tools, but what about the next wave of thinking professionals? Do pilots and surgeons analyze information in Excel when they need to make splitsecond decisions? Or do they simply glance at equipment consoles to assess the status of current conditions? Like most business professionals, these decision-makers need simple-to-use BI apps. To make BI pervasive in the enterprise, users of all types and skill levels should be able to explore and analyze data in the way they are most comfortable: Information specialists and developers need easy-to-use tools to deliver dashboards and reports quickly for all users Non-technical business users want simple InfoApps to explore and analyze their data Analysts need easy-to-use, powerful visualization tools Customers and partners want ways to analyze personal and peer data for new insights 2 Data Discovery in the Enterprise

5 In all cases, if you deploy a visualization tool without the required expertise, you risk creating a ton of graphics that don t translate to real, actionable insights. Check Scalability Wayne Eckerson, principal consultant, Eckerson Group, says, Pure-play visual discovery tools were not designed to handle enterprise deployments. Besides scalability, most vendors haven t invested significantly in failover, load balancing, disaster recovery, clustering, monitoring, and administration capabilities. 2 This makes these tools less than ideal for wide-scale deployment, especially when going outside the firewall to meet the analytical needs of external audiences like customers, suppliers, and partners. And because most data discovery tools rely on in-memory analytics to optimize processing speed, performance will degrade substantially as the number of users and the amount of data grows. This is something that companies with big data analytics strategies need to consider. Don t Ignore Real-Time Operational Needs For the best results, BI should work on three interconnected levels: strategic, analytic, and operational. Strategic analysis drives analytical BI, which directs the focus of operational initiatives. Operational BI facilitates the kind of day-to-day decision-making that happens at the lower levels of an organization the scores of employees on the front lines, on the shop floor, in the delivery truck, on the sales team, and in the call center. Operational BI can directly impact the company s ability to reach objectives such as increased sales or greater profitability. Operational BI is proactive. It reduces the gap between the discovery of problems or opportunities and taking action on them. It can also embed corrective action into business processes. To support operational BI initiatives, you need efficient, powerful integration technology to access and interconnect all data especially real-time data. That s not possible with most data discovery tools without complicated partnering strategies and add-ons. If you are looking to analyze real-time data, data discovery tools are probably not right for you. Many use static pre-loaded data, rather than live data from an external data source. 2 Eckerson, Wayne. Visual Discovery Tools: Market Segmentation and Product Positioning, Eckerson Group, March Information Builders

6 2 Are Rogue Dashboards Creating More Questions Than Answers? With every dashboard, you have to wonder: Is the data accurate? Is the analytical method correct? Is there bias in the presentation of the data? Most importantly, can we base critical business decisions on this information? Like Excel and OLAP cubes from back in the day, most data discovery tools lack enterprise-class version control and auditing ability. Users may enhance the visual appeal of the information being analyzed, but they re disconnected from the enterprise environment. They are working with their own data sets, and have their own means of manipulating and sharing information. The result? Rogue dashboards that permeate the enterprise in a completely disjointed and uncontrolled fashion. In this data visualization wild west, users modify data and change fields with no audit trail and no way to tell who changed what. This disconnect can lead to inconsistent insight and flawed decisions, drive up administration costs, and inevitably create multiple versions of the truth, with users arriving at different conclusions. Having an enterprise-wide data governance policy will help mitigate the risk of a data breach. This includes defining rules and processes related to dashboard creation, ownership, distribution, and usage; creating restrictions on who can access what data; and ensuring that employees follow their organizations data usage policies. Many data discovery toolsets do not offer metadata management and data integrity solutions as part of the package; you have to buy them separately, which complicates business processes and workflows unnecessarily. Security also poses a problem with data discovery tools. IT staff typically have little or no control over these types of solutions, which means they can t protect sensitive information. This can result in unencrypted data being cached locally and viewed by or shared with unauthorized users. In addition, heed these cautions when evaluating data discovery toolset security: Geared towards departmental implementation, not large-scale rollouts to multiple user communities May be difficult to integrate with single sign-on solutions Can t easily administer security at multiple levels Not robust, hardened enterprise solution out of the box Bottom line: If the toolset doesn t offer adequate data management and security, it s not suitable for the enterprise market. 4 Data Discovery in the Enterprise

7 3 How Do We Ensure Data Integrity and Prevent Flawed Insights? What s one of the biggest issues facing visual analytics? Organizations are offering data visualization as an easy way into pattern recognition, but there is a danger in drawing conclusions from data visualizations without drilling down and looking at the base data for clarification. Pattern detection is not a new discipline. Statisticians have long used algorithms (i.e., data mining) to derive insights from data. If you re not careful, however, those insights may be flawed. Take the Simpson Paradox, a phenomenon that can distort causal relationships in data sets due to a lurking variable. A popular example of this is a study that shows that dieting is much more effective than exercise, but the opposite is true when you break it down by Body Mass Index. The percentage of patients who lost weight was higher for exercisers, but when you aggregate the data, the dieters appear to do better. Correlation on aggregate levels can be completely different on the base level, which is why anyone using a visualization tool to back up a decision must be able to easily see and understand the relationships in the underlying data. That s why metadata matters. Many data discovery tools lack the control, reusability, and analytical integrity of metadata management. Users must truly know and understand the information they are working with in order to effectively use the tools and reap full value from them. Furthermore, the process of pattern discovery in data frequently involves multiple steps to prepare the data for analysis. Such steps include creating new subsets from existing data sets where the subset is obtained either by filtering, aggregating, or grouping the original data in some manner. Those subsets can be matched or merged with other data sets to create entirely new sets. New fields and variables can be added via calculations and statistics. In the process, analysts use complex logical operators such as union, intersect, subtract, append, and others making the possibility for errors significant. Any error would exaggerate or diminish the results. That s why BI platform vendors have created sophisticated methods and user interfaces to manage those operations. They include not only the right set of operators but also graphical tools like Venn diagrams to guide the user through the process. Simple data blending leaves the analyst to his own devices in the complex world of data preparation. Poor data quality also poses a huge problem with data discovery tools. Pure-play BI vendors haven t sufficiently addressed enterprise data management issues, such as data quality, data profiling, data transformation, metadata management and team-based development, says Eckerson. 3 Data discovery tools expect relatively clean data in a tabular format. They do not provide profiling, cleansing, or standardizing of enterprise information. If your organization is like most, with data error rates of between 1 percent and 5 percent, you re exposing a massive problem. 4 The point of effective visualization is to design and implement dashboards that communicate correctly. Companies that employ data discovery tools may generate beautiful graphics, but the information they depict may be misleading, inaccurate, or invalid. 3 Eckerson, Wayne. Visual Discovery Tools: Market Segmentation and Product Positioning, Eckerson Group, March Redman, Thomas C. The Impact of Poor Data Quality on the Typical Enterprise, Communications of the ACM, February Information Builders

8 4 What Costs Are Associated With In-Memory Limitations? Today s users need to efficiently access and analyze large data volumes for a variety of critical purposes. One popular approach among some vendors has been to create physical OLAP cubes that pre-calculate every possible aggregate combination across multiple dimensional attributes. Although this does increase performance, physical cubes have trouble supporting large data volumes and are inflexible when business needs change. Customer Success Snapshot: Torstar Digital The Organization Torstar Digital is one of Canada s leading digital media organizations. The Challenge Limited reporting capabilities in Torstar s NetSuite systems forced it to devote more resources to generating Excel-based reports not a sustainable approach. Torstar needed to improve users ability to access and analyze information from NetSuite, ad servers, and other sources. The Solution After considering several options, including standalone data discovery tools from Tableau, Torstar determined that Information Builders WebFOCUS BI platform was the best approach. The Result Faster access to important information drives better advertising decisions, while increased user self-sufficiency and reduced reliance on Excel frees up valuable resources. Another common technique is to put all of the data into server RAM to take advantage of the inherent I/O rate improvements over disk. This technique has been very successful and spawned a trend of using in-memory analytics for increased BI performance. But in-memory analytic solutions struggle to maintain performance as the size of the data goes beyond the fixed amount of server RAM. For in-memory solutions to scale, they need a lot of hardware and a complex multi-node sever deployment. That means either hiring someone with the right technical skills to administer the environment, or purchasing pre-built appliances that contain multiple nodes both high-cost options. For companies experiencing lagging query response times due to large data volumes or a high volume of ad hoc queries, consider a hybrid solution a robust, column-oriented data store that s an integrated part of the BI platform. This approach delivers a formidable self-managing environment optimized for reporting and analytics. It not only improves performance, but also eliminates cumbersome database administration and reduces total cost of ownership. 6 Data Discovery in the Enterprise

9 Using both RAM and disk offers the high performance of in-memory analytics with minimal hardware. Data discovery vendors would need significantly more CPU, RAM, and sometimes multiple servers to achieve the same performance as a column-oriented data store on a fast and flexible BI platform. 7 Information Builders

10 5 Can You Add Advanced Analytic Capabilities With Ease? A huge functionality gap exists between BI platforms and data discovery tools. Data discovery vendors offer very narrow capabilities that are limited primarily to visualization and dashboarding. They lack more complete BI functionality, such as: Complex queries, such as those that require data from multiple applications and databases Ad hoc query capabilities, so power users can easily generate their own reports and analyses Predictive analytics, which leverages patterns and trends in historical data to forecast future events and outcomes Performance management, to monitor and track metrics and KPIs Reporting and distribution, which makes information available to the right people in the right context Enterprise search apps, so structured and unstructured information is easier to index and locate Social media analytics, for tapping into real-time sentiment from Facebook, Twitter, surveys, and other sources Disconnected analytics, so users can interact with enterprise data even when no Internet connection is available Customer Success Snapshot: Houston Police Department The Organization The Houston, TX PD is the nation s fourth-largest law enforcement agency, with 5,200 officers and 1,300 civilian employees. The Challenge Find faster, more effective ways to tap into a massive data warehouse, enriched by numerous external sources and containing more than 15 years of historic crime data. Because analysis was conducted using handwritten SQL requests or complex Microsoft Access queries, only specialists could retrieve timely information to help improve public safety. The Solution To empower a broad audience of users to access and analyze a large volume of data, the department needed more than just individual dashboards; it needed a comprehensive BI platform. The Result Information Builders integration and intelligence technologies are the backbone of a real-time crime center that collects critical data and pushes it directly to officers via their mobile devices. Dashboards allow chiefs and captains to better manage their districts by tracking crime statistics and trends in real time. 8 Data Discovery in the Enterprise

11 Furthermore, most data discovery tools: Offer limited integration with Microsoft Office Make it difficult and costly for large numbers of external users to analyze and visualize information when they are offline Provide no support for portals or mash-ups Don t offer write-back capabilities, so users cannot modify or update data directly from the analytic environment to reflect new activities or changing business conditions Lack customization and personalization, so users are stuck with a standard look and feel, and developers have little flexibility in how information is presented to end users Offer very limited interactivity These limitations can hinder adoption, because the needs of just a small portion of the user base will be effectively met. The rest of the audience will be forced to find other ways to manipulate, analyze, and share information to meet their unique and specific needs. With business intelligence, you have an opportunity to create a virtuous cycle of smarter decisionmaking by fully leveraging information assets across the user spectrum. To do this, you must go beyond the narrow scope of data visualization and satisfy the needs of all your users: information specialists, analysts, executives, operational employees, partners, suppliers, and customers. This requires a fast, flexible, and easily extensible BI platform that offers depth and breadth of BI, reporting, and analytical capabilities. 9 Information Builders

12 What It Takes: A Fast and Flexible BI and Analytics Platform Progressive companies consider data to be a strategic asset and understand its importance for driving innovation, differentiation, and growth. But leveraging data and transforming it into real business value requires a new approach to BI and analytics beyond the scope of most data visualization tools and dramatically different than the clunky BI platforms of years past. Information Builders has the answer: WebFOCUS, a fast and flexible BI and analytics platform that offers data visualization, plus other core and advanced capabilities. Not all BI platforms are the same. Many traditional platforms are a patchwork of disconnected modules, evolving chiefly through mergers and acquisitions. Quite the opposite, WebFOCUS has evolved organically to meet the business demands and requirements of enterprise customers. Other platforms are heavy and cumbersome to use, or too complicated to satisfy a wide variety of user communities. And some are too lightweight and provide only niche or departmental solutions. Looking good is only half the battle when choosing a data visualization solution; good looks are useless without clean, consistent, accurate data that can be accessed by all users at all times from any location. 10 Data Discovery in the Enterprise

13 WebFOCUS hits the enterprise sweet spot. Because different people need different kinds of information, WebFOCUS lets you choose the right approach for the right person. Whether it s compelling data visualizations and dashboards, powerful analytical tools to solve challenging business problems, interactive e-statements to improve the customer experience, broad-scale operational BI, in-depth financial and regulatory reporting, or self-service InfoApps for people who need specific information at a glance, WebFOCUS has you covered. Unlike data discovery tools, WebFOCUS lets users conduct analyses and manipulate data the way they want. Whether they want spreadsheets, sophisticated visualizations, or pre-built BI apps, WebFOCUS will satisfy everyone s needs, while centralizing administration and preserving data integrity, consistency, and auditing ability. Here s a run-down of why WebFOCUS is the smart choice for data visualization and self-service analytics: Customer Success Snapshot: La Caixa The Organization La Caixa is Spain s largest savings bank, with more than nine million customers. The Challenge Accelerate growth by empowering sales executives in more than 4,700 branches to identify prospects, develop targeted campaigns, and close new deals. The Solution A self-service BI and reporting environment, built on WebFOCUS, allows sales executives to analyze more than 1,000 variables for each customer, to identify those with the greatest likelihood of purchasing certain products or services. Customer information is accessed through an intuitive BI portal that requires no training. The Result With the new environment, La Caixa has grown its SMB customer base by 9 percent in just 10 months, and has increased profitability in this segment by 6 percent. Self-Service Analytics for Everyone WebFOCUS delivers a broad range of features and capabilities, so the right tools are available to all the right people on the right device. For example, you can empower: Information specialists and developers with easy-to-use tools and a BI portal to deliver dashboards and reports quickly to all users Non-technical business users with simple InfoApps to explore and analyze their data Analysts and information specialists with easy-to-use and powerful visualization tools Customers and partners with ways to gain new insights from personal and peer data 11 Information Builders

14 And WebFOCUS ensures everyone has consistent and accurate data even when you are dealing with a variety of complex data sources. Centralized Management and Security The most successful way to enable enterprise-caliber data discovery is to keep people connected and ensure a single, consistent view of enterprise information even if different features and capabilities are used to perform analyses. This is something that only a comprehensive BI platform with centralized management can do. A flexible, extensible BI platform offers a wide array of functionality, including centralized management, to eliminate the drawbacks of standalone data discovery tools while letting users conduct sophisticated analyses and manipulate data the way they want. Big Data Analytics Performance WebFOCUS also offers Hyperstage, an embedded data store that dramatically improves performance. WebFOCUS Hyperstage uses a hybrid approach that combines the I/O advantage of in-memory analytics with an intelligent architecture that allows data to be stored on disk without sacrificing performance. Hyperstage can scale up to many terabytes, while many other in-memory solutions are restricted to a couple of hundred gigabytes. Scalability WebFOCUS is the most scalable business intelligence solution on the market. An innovative architecture with features such as non-persistence, server multi-threading, cluster management and load balancing, and built-in stress testing make more information available to more people, while minimizing the amount of hardware, software, and staff required to implement and maintain the environment. Built-In Data Quality A comprehensive BI platform with embedded data quality management capabilities can ensure optimum integrity in all visualizations, especially when drawing data from complex, disparate systems. Only Information Builders offers a common, unified environment to simultaneously address analytical and data integrity needs. Information Builders iway integrity solutions are fully integrated with WebFOCUS, and are designed to enhance the accuracy and consistency of enterprise information throughout its lifecycle. Organizations can eliminate the data quality pitfalls associated with data discovery tools, and guarantee that the data presented in visualizations is correct and complete at all times. 12 Data Discovery in the Enterprise

15 From profiling, standardization, and validation, through unification, cleansing, enrichment, and ongoing data governance, the iway Data Quality Suite provides a broad-reaching, highperformance environment that enables truly proactive data quality management. Organizations can create a real-time data quality firewall that not only locates and rectifies invalid or corrupt information in enterprise systems, but stops it from entering the environment in the first place. Robust Data Visualization Capabilities WebFOCUS provides deep, sophisticated visual analysis of any enterprise data. Information can be displayed in scatter plots, 3D bar and pie charts, histograms, data constellations, multiscapes, and other cutting-edge visualizations, so users can perform in-depth analysis in real time without the need for disconnected data discovery tools. In addition to providing next-generation data discovery tools for analysts, WebFOCUS also offers an easy way to deploy data discovery apps to a wide variety of end users. This allows you to produce, for example, reports, dashboards, and InfoApps with embedded data discovery functionality. Most importantly, all WebFOCUS content can be easily assembled into intuitive portals, and accessed via any smartphone or tablet. And WebFOCUS Active Technologies can be used to combine data, charting, and interactive analytic capabilities into a single web document that can be ed and saved offline. Any number of internal and external users can interact with data, without installing any specialized software, even when they are disconnected. BI Portal The WebFOCUS BI Portal is like a dynamic content management system for your BI content, including dashboards, reports, charts, graphs, maps, and interactive InfoApps. It allows users to quickly access and analyze vital information, link content and reports together, and easily tailor what they see. Tools and Apps With WebFOCUS, BI portals and InfoApps can be easily deployed to any number of users inside or outside the enterprise. For example, InfoApps can be easily embedded into SaaS applications for customers and business partners. Portals and InfoApps can also be easily accessed on any smartphone or tablet, or even used offline, so business professionals can interact with data via their device of choice, even when they are unable to connect to the web. 13 Information Builders

16 Conclusion Data discovery tools are nothing more than slicker versions of Excel. They enhance the visual appeal of the information being analyzed, but they still create the risk of inconsistent insight and flawed decisions because they lack version control and auditing ability, and have no means of ensuring ensure data integrity. In addition, standalone data discovery tools are notoriously expensive, for these key reasons: They don t provide a metadata layer, making them geared more towards business analysts and other power users They lack centralized management tools, which can create a tremendous administration burden for IT departments. Pricing models for today s data discovery tools often require organizations to purchase licenses (which can cost more than $1,000 each) for all users even those who are simply viewing content created by others According to Gartner s Rita Sallam, the cost of supporting individual users currently tends to be higher with data discovery tools 5 WebFOCUS is designed to keep total cost of ownership at a minimum by addressing the full spectrum of user needs, from developers to information consumers. Server-based licensing helps to keep expenses down in enterprise scenarios. Visually compelling, highly interactive self-service applications and InfoApps with advanced visualization and analysis capabilities can be made accessible to an unlimited number of internal and external users, on any device. No specialized software to install and run, and no individual licensing, per user, or per seat cost. The time has come to visualize responsibly. Organization need to move away from rogue and disconnected spreadsheets, dashboards, and visualizations by implementing a comprehensive BI platform that delivers state-of-the-art visualization capabilities plus other advanced analytical functionality in a centralized, easy to manage environment. To see how beautiful and responsible data visualizations can be, watch this 30-minute demo, InfoApps and Data Visualization. 5 Brunell, Mark. Gartner Magic Quadrant: Data Discovery Vendors Take on BI Heavyweights, TechTarget, February Data Discovery in the Enterprise

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