I am happy to offer some insights on Tableau drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research. We utilized a structured research methodology that includes evaluation categories designed to reflect the breadth of the real-world criteria incorporated in a request for proposal (RFP) and vendor selection process for analytics and business intelligence. We evaluated Tableau and 14 other vendors in seven categories, five relevant to the product (adaptability, capability, manageability, reliability and usability) and two related to the vendor (TCO/ROI and vendor validation). To arrive at the Value Index rating for a given vendor, we weighted each category to reflect its relative importance in an RFP process, with the weightings based on our experience and data derived from our benchmark research on analytics and business intelligence.
Topics: Data Science, Tableau, Mobile Technology, Analytics, Business Intelligence, Cloud Computing, Collaboration, Digital Technology
More than 13,000 self-described “data and visualization nerds” gathered in Austin, TX, recently for Tableau Software’s annual customer conference. In his inaugural keynote, Tableau’s new CEO, Adam Selipsky, said that nearly 9,000 were first-time attendees. I was impressed with the enthusiasm of the customers who had gathered for the event, cheering as company officials reviewed product plans and demonstrated new features. This enthusiasm suggests Tableau has provided capabilities that resonate with its users. Among other things, the company used the conference to outline a number of planned product enhancements.
Topics: Tableau, Analytics, Business Intelligence, Visualization, DataPrep
Tableau Software’s annual conference, which company spokespeople reported had more than 10,000 attendees, filled the MGM Grand in Las Vegas. Various product announcements supported the company’s strategy to deliver value to analysts and users of visualization tools. Advances include new data preparation and integration features, advanced analytics and mapping. The company also announced the release of a stand-alone mobile application called Vizable . One key message management aimed to promote is that Tableau is more than just a visualization company.
Topics: Big Data, Tableau, Mobile Technology, data viz, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Governance, Risk & Compliance (GRC), Information Management, Operational Intelligence, Visualization, Information Optimization, Risk & Compliance (GRC)
Qlik was an early pioneer in developing a substantial market for a visual discovery tool that enables end users to easily access and manipulate analytics and data. Its QlikView application uses an associative experience that takes an in-memory, correlation-based approach to present a simpler design and user experience for analytics than previous tools. Driven by sales of QlikView, the company’s revenue has grown to more than $.5 billion, and originating in Sweden it has a global presence.
Topics: Big Data, Data Visualization, QlikView, Sales Performance, Supply Chain Performance, Tableau, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Information Applications, Data Discovery, Lumira, Qlik, Qlik Qlik Sense
Ventana Research recently completed the most comprehensive evaluation of mobile business intelligence products and vendors available anywhere today. The evaluation includes 16 technology vendors’ offerings on smartphones and tablets and use across Apple, Google Android, Microsoft Surface and RIM BlackBerry that were assessed in seven key categories: usability, manageability, reliability, capability, adaptability, vendor validation and TCO and ROI. The result is our Value Index for Mobile Business Intelligence in 2014. The analysis shows that the top supplier is MicroStrategy, which qualifies as a Hot vendor and is followed by 10 other Hot vendors: IBM, SAP, QlikTech, Information Builders, Yellowfin, Tableau Software, Roambi, SAS, Oracle and arcplan.
Topics: Big Data, MicroStrategy, Mobile, Mobile Business Intelligence, Pentaho, Sales Performance, SAP, SAS, Tableau, Jaspersoft, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Customer & Contact Center, IBM, Information Builders, Oracle, Workforce Performance, Yellowfin, Roambi, Value Index, arcplan, Logi Analytics, Qlik
Microsoft has been steadily pouring money into big data and business intelligence. The company of course owns the most widely used analytical tool in the world, Microsoft Excel, which our benchmark research into Spreadsheets in the Enterprise shows is not going away soon. User resistance (cited by 56% of participants) and lack of a business case (50%) are the most common reasons that spreadsheets are not being replaced in the enterprise. The challenge is ensuring the spreadsheets are not just personally used but connected and secured into the enterprise for a range of consistency and potential errors that all add up to more work and maintenance as my colleague has pointed out recently.
Topics: Big Data, Microsoft, Tableau, IT Performance, Microsoft Office, Microsoft Powerpoint, Operational Performance, Business Analytics, Business Intelligence, Business Performance, CIO, Cloud Computing, Customer & Contact Center, Financial Performance, Hortonworks, Information Applications, Location Intelligence, Microsoft Excel, azure, HDinsights
Teradata recently gave me a technology update and a peek into the future of its portfolio for big data, information management and business analytics at its annual technology influencer summit. The company continues to innovate and build upon its Teradata 14 releases and its new processing technology. Since my last analysis of Teradata’s big data strategy, it has embraced technologies like Hadoop with its Teradata Aster Appliance, which won our 2012 Technology Innovation Award in Big Data. Teradata is steadily extending beyond providing just big data technology to offer a range of analytic options and appliances through advances in Teradata Aster and its overall data and analytic architectures. One example is its data warehouse appliance business, which according to our benchmark research is one of the key technological approaches to big data; as well Teradata has advanced support with its own technology offering for in-memory databases, specialized databases and Hadoop in one integrated architecture. It is taking an enterprise management approach to these technologies through Teradata Viewpoint, which helps monitor and manage systems and support a more distributed computing architecture.
Topics: Big Data, MicroStrategy, SAS, Tableau, Teradata, Customer Excellence, Operational Performance, Analytics, Business Analytics, Business Intelligence, CIO, Cloud Computing, Customer & Contact Center, In-Memory Computing, Information Applications, Information Management, Location Intelligence, Operational Intelligence, CMO, Discovery, Intelligent Memory, Teradata Aster, Strata+Hadoop
Our benchmark research found in business technology innovation that analytics is the most important new technology for improving their organization’s performance; they ranked big data only fifth out of six choices. This and other findings indicate that the best way for big data to contribute value to today’s organizations is to be paired with analytics. Recently, I wrote about what I call the four pillars of big data analytics on which the technology must be built. These areas are the foundation of big data and information optimization, predictive analytics, right-time analytics and the discovery and visualization of analytics. These components gave me a framework for looking at Teradata’s approach to big data analytics during the company’s analyst conference last week in La Jolla, Calif.
Topics: Big Data, MicroStrategy, Tableau, Teradata, alteryx, IT Performance, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Governance, Risk & Compliance (GRC), IBM, Information Applications, Information Management, Operational Intelligence, Oracle
This year’s Inspire, Alteryx’s annual user conference, featured new developments around the company’s analytics platform. Alteryx CEO Dean Stoecker kicked off the event by talking about the promise of big data, the dissemination of analytics throughout the organization, and the data artisan as the “new boss.” Alteryx coined the term “data artisan” to represent the persona at the center of the company’s development and marketing efforts. My colleague Mark Smith wrote about the rise of the data artisan in his analysis of last year’s event.
Topics: Predictive Analytics, Sales Performance, Tableau, alteryx, Absolute Data, data artisan, Operational Performance, Analytics, Business Analytics, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Data Integration, Information Applications, Operational Intelligence
SiSense gained a lot of traction last week at the Strata conference in San Jose as it broke records in the so-called 10x10x10 Challenge – analyzing 10 terabytes of data in 10 seconds on a $10,000 commodity machine – and earned the company’s Prism product the Audience Choice Award. The Israel-based company, founded in 2005, has venture capital backing and is currently running at a profit with customers in more than 50 countries and marquee customers such as Target and Merck. Prism, its primary product, provides the entire business analytics stack, from ETL capabilities through data analysis and visualization. From the demonstrations I’ve seen, the toolset appears relatively user-friendly, which is important because customers say usability is the top criterion in 63 percent of organizations according to our next-generation business intelligence.
Topics: Big Data, Sales Performance, Tableau, elasticube, Operational Performance, Analytics, Business Intelligence, Business Performance, Customer & Contact Center, Information Applications, Information Management, Qlik
I recently returned from Sweden, where QlikTech International hosted its annual analyst “unsummit.” Much of the information I was exposed to was under NDA, so I cannot talk about it here. What I can discuss, and what in many ways may be more interesting and more important, is the company’s focus on culture and philosophy.
Topics: Big Data, Data Visualization, QlikView, Tableau, Google, discovery analytics, exploratory analytics, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Cloud Computing, Customer & Contact Center, Information Applications, Location Intelligence, Operational Intelligence, Workforce Performance, Impala, big query, Qliktech
Tableau Software is growing fast. Tableau has taken a “land and expand” strategy that drives what they call the democratization of analytics within organizations. Tableau has enjoyed first mover advantage in the area of exploratory analytics called visual discovery, a growing type of business analytics that allows companies to easily visualize data in a descriptive manner, but the company is facing competition as deep-pocket companies such as IBM, SAP and others become more aggressive in the space.
Topics: Big Data, Data Visualization, Sales Performance, Tableau, Google, discovery analytics, exploratory analytics, Operational Performance, Analytics, Business Analytics, Business Collaboration, Business Intelligence, Business Performance, Customer & Contact Center, Operational Intelligence, Impala, big query
Tableau Software officially released Version 6 of its product this week. Tableau approaches business intelligence from the end user’s perspective, focusing primarily on delivering tools that allow people to easily interact with data and visualize it. With this release, Tableau has advanced its in-memory processing capabilities significantly. Fundamentally Tableau 6 shifts from the intelligent caching scheme used in prior versions to a columnar, in-memory data architecture in order to increase performance and scalability.
Topics: Data Visualization, Enterprise Data Strategy, Tableau, Analytics, Business Analytics, Business Intelligence, CIO, In-Memory Computing