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Data Discovery Hype
1.
© ۲۰۱۵ IBM
Corporation Market and Competitive Overview The Data Discovery Hype Julie Severance IBM Analytics Strategy & Initiatives
2.
© 2015 IBM
Corporation 2 Explore, review and share key findings on the current marketplace Data Discovery Hype. Sources of research: • Gartner • IDC • Internal Resources • External Resources Goals of this presentationGoals of this presentation
3.
© 2015 IBM
Corporation 3 Data Discovery – BI & Analytics LandscapeData Discovery – BI & Analytics Landscape Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms 2013-2015
4.
© 2015 IBM
Corporation 4 Data Discovery - Next GenerationData Discovery - Next Generation Buyers: IT department Sellers: megavendors/large independents Approach: top-down, existing repositories queried User interface: report, dashboard or grid Use case: monitoring, reporting Buyers: Line of business Sellers: smaller, independent Approach: bottom-up, moved to dedicated repository User interface: data visualization Use case: analysis Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms, 2015 Big, Trusted BI Platforms Data Discovery Tools
5.
© 2015 IBM
Corporation 5 SmartVisual Data Discovery – AttributesData Discovery – Attributes Governed DATA DISCOVERY Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms, 2015
6.
© 2015 IBM
Corporation 6 Hype Cycle for Business Intelligence & Analytics Platforms Benefit: High Years to mainstream: Less than 2 Years Market Penetration: 1% to 5% of target audience Benefit: Moderate Years to mainstream: Less than 2 Years Market Penetration: 20% to 50% of target audience Benefit: Transformational Years to mainstream: 2 to 5 years Market Penetration: 1% to 5% of target audience Data Discovery – Hype CycleData Discovery – Hype Cycle
7.
© 2015 IBM
Corporation 7 Data Discovery – Market ShareData Discovery – Market Share 50% 8.9% • Declining BI revenues • Months to implement • IT-centric deployment • Revenues growing 78% and 17% • Days and weeks to implement • Business-centric deployment 6.2% Source: Gartner Investor Advisory Day, 9/2015 MARKET SHARE
8.
© 2015 IBM
Corporation 8 Data Discovery – Market Size, RevenueData Discovery – Market Size, Revenue Visual data discovery tools will grow 2.5x faster than the rest of the BI tools market. - IDC MARKET SIZING Projected to grow at a compound annual growth rate (CAGR) of 8.7% through 2018. MARKET REVENUE Qlik – $ 205 million Tibco Spotfire – $70.5 million Tableau – $38 million SAS (JMP) – $35 million Microsoft PowerPivot – $25 million. Microstrategy Visual Insight Advizor Solutions. <$ 10 million
9.
© 2015 IBM
Corporation 9 Source: Gartner Magic Quadrant for Advanced Analytics Platforms, 2014 - 2015 Data Discovery – Advanced Analytics LandscapeData Discovery – Advanced Analytics Landscape
10.
© 2015 IBM
Corporation 10 Dashboards Smart Data Discovery Content Pre-set metrics and KPIs Best visualization Interaction Predefined Free form, Natural language Data prep IT-modelled Autodiscovery and self-service ETL Data Summary, data warehouse Big data, cloud Analysis Descriptive, some diagnostic Autodiagnostic, predictive and prescriptive Vendors Traditional, data discovery, dashboard pureplays Data Discovery - Future TrendsData Discovery - Future Trends Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms, 2015 IBM Watson Analytics
11.
© 2015 IBM
Corporation 11 Data Discovery – Strategic approach for growthData Discovery – Strategic approach for growth
12.
© 2015 IBM
Corporation 12 Data Discovery - Issues and challengesData Discovery - Issues and challenges Through 2016, less than 10% of self-service business intelligence initiatives will be governed sufficiently to prevent inconstancies that adversely affect the business. Opportunity to introduce AQ best practice guidance on how to evolve maturity and build a case for an analytics program (ACE). Multiple versions of the truth. Data discovery tools are regularly being sold directly to business units and business users. This is in contrast to the traditional BI sales into IT. This can lead to multiple spreadmarts springing up, and multiple versions of the truth. The flip side is that much of this can be managed and controlled if there is collaboration between the business and IT. So IT implements and manages the solution, metadata libraries & business glossaries. Opportunity to introduce AQ best practice guidance on how to evolve maturity and build a case for an analytics program (ACE). This also could open discussions up around CAO/CDO.
13.
© 2015 IBM
Corporation 13 Ease of Use Speed to Discovery Cost of Entry Have a plan for the future 1 2 3 4 5 6 Data Discovery – Key Success FactorsData Discovery – Key Success Factors Quality of Visualization/ Interactively/ Portability Cost to incorporate future requirements
14.
© 2015 IBM
Corporation 14
15.
© 2015 IBM
Corporation Market and Competitive Overview The Data Discovery Hype Julie Severance IBM Analytics Strategy & Initiatives
16.
© 2015 IBM
Corporation 2 2 Explore, review and share key findings on the current marketplace Data Discovery Hype. Sources of research: • Gartner • IDC • Internal Resources • External Resources Goals of this presentationGoals of this presentation
17.
© 2015 IBM
Corporation 11/12/15 3 3 Data Discovery – BI & Analytics LandscapeData Discovery – BI & Analytics Landscape Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms 2013-2015 In 2014 there was a new split between BI and Analytics Platforms and Advanced Analytics Platforms. Data Discovery is a response to the current market place data explosion hype. – it goes on and sites data discovery tools that satisfy the needs of business users on the front end and IT workers on the back end as the top priority for businesses. Unfortunately, the Garner analysts see no clear-cut vendor offering that can handle all these needs. The main challenge is governance. While the top vendors in the space largely remained the same over the last 3 years -- the report notes that they all moved to the left of the quadrant, indicating a lower "completeness of vision" score. The report states that no vendor is addressing the need for "governed data discovery." Finding the right balance between an open self-service environment that empowers users while at the same time maintaining high standards for data quality and other data management best practices remains a challenge. Emerging data discovery tools tend to be light on governance, while discovery applications from more established vendors may be subpar, the report says. On the bright side, the report notes that a number of established vendors -- Microsoft, MicroStrategy and SAS -- are getting better at integrating data discovery capabilities. Additionally, Qlik, Tableau and Tibco are planning new releases. While the market may lack a clear leader in data discovery, buyers will have new options in 2014. In 2015, the analyst firm decided to break off advanced analytics systems from its standard Business Intelligence and Analytics Platforms Magic Quadrant. The new report focuses on vendors offering predictive analytics, data mining and other types of algorithm-based analysis tools. Gartner felt it needed to give this market its own report mostly because of heavy interest from business. That interest is being driven by a growing need for sophisticated tools that can handle big data. Data sets are growing and new sources are emerging, including social and sensor data. Traditional BI tools can't keep up. IBM and SAS distanced themselves from the pack in the inaugural advanced analytics Magic Quadrant -- IBM for its relative ease of use and SAS for customer satisfaction. Other vendors, such as RapidMiner, KNIME and Revolution Analytics also received high marks. Expect the market to continue to develop, though. The report notes that most products are currently focused mainly on prediction, but businesses are increasingly looking for products that can handle marketing or spending optimization and run simulations.
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Corporation 11/12/15 4 4 Data Discovery - Next GenerationData Discovery - Next Generation Buyers: IT department Sellers: megavendors/large independents Approach: top-down, existing repositories queried User interface: report, dashboard or grid Use case: monitoring, reporting Buyers: Line of business Sellers: smaller, independent Approach: bottom-up, moved to dedicated repository User interface: data visualization Use case: analysis Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms, 2015 Big, Trusted BI Platforms Data Discovery Tools Data discovery software vendors are stealing market share from the leading business intelligence (BI) players, according to the recent Gartner Magic Quadrant for BI Platforms report. Independent data discovery software companies are muscling in on territory that once belonged to business intelligence (BI) megavendors like Oracle and SAP BusinessObjects, according to a new Gartner Magic Quadrant report. The findings represent a sea change in attitude that is being driven largely by business users who want ease of use and who are exerting more influence over BI purchasing decisions than ever before. Historically viewed as a supplement to traditional BI platforms, data discovery software is now increasingly being sought as a viable standalone alternative. “That ease-of-use dynamic -- the fact that the business users are having greater influence over the purchasing decision -- is really driving the momentum of data discovery vendors like Tableau, Tibco Spotfire, and QlikTech,” said Rita Sallam, a BI research director with Stamford, Conn.-based Gartner Inc. “They’ve been on the Magic Quadrant [before] but this year we’ve seen the momentum pick up.” Several factors appear to be driving the high pace of adoption. Usability —Usability is the No. 1 selection criterion when choosing BI tools, according to Gartner’s “Magic Quadrant for Business Intelligence Platforms. Strong visualization capabilities, intuitive user interfaces and fast query times put visualization tools in this usability sweet spot. Time to deliver — A light footprint means these tools can typically be deployed quicker than traditional BI platforms. This is particularly attractive for departmental type implementations where enterprise scale BI solutions can feel like an overkill The speed to deliver can be particularly quick when Visualisation tools are provided via Software as a Service (SaaS). Efficient proof of concept : Sales organizations often can do proof-of-concepts much more quickly, thereby shortening the sales cycles. The promise of being able to cut through to answers. Visualization–analytics are often sold on the promise of being flexible enough to answer multiple questions and ultimately answer business problems much quicker than traditional BI tools.
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Corporation 11/12/15 5 5 SmartVisual Data Discovery – AttributesData Discovery – Attributes Governed DATA DISCOVERY Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms, 2015 What is data discovery? Is it something real or is it just another in a long string of buzzwords invented by someone in marketing to instill a new need to product or differentiate it from the competition? Wikipedia states this definition: “Data discovery is a business intelligence architecture aimed at interactive reports and explorable data from multiple sources.” Gartner is a little more expansive: ”Data discovery software and traditional BI platforms offer similar capabilities. But there are some important differences.” Gartner explains that with traditional business intelligence, the buyers are in the IT department, the user interface is in the form of reports, dashboards, or grids, and it is primarily used for monitoring and reporting. It says that for data discovery, the buyers are the business workers, the user interface is through data visualization, and it is primarily used for analysis. The fact is that, until you get into the data, not only don’t you have all of the answers, you may not even have all of the questions. Unanticipated questions mean that you may not have the right data on the screen to address the question when it forms in your mind. Data discovery allows you to explore the data to answer those questions that pop up as you look at the data. Sometimes that means looking at the data in a new way—a rich visualization instead of a table, a heat map instead of a scatter plot. Sometimes it means including more data in your universe—does the sales data beg a question about customer loyalty? Do you need to grab some customer history data? Sometimes it means enriching your data with calculations and classifications. Users who are both data-driven and “creators” or “analyst” (“Detectives” according to Aberdeen), use data discovery tools “to freely explore pertinent data and approach business problems from a new angle.” They frequently don’t know where the data will lead them, but the use the data to inform the decision at hand. So a data detective might look at a P&L and see something that looks out of place. From there, they may want to drill into the data to see transaction detail. But that might spark another question related to the sales region, so she might need to drag the sales data onto the screen along with the financial data and then do some visual trend analyses to pinpoint a problem or opportunity. A data discovery tool will allow the user to do all of this in real time without IT intervention.
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Corporation 11/12/15 6 6 Hype Cycle for Business Intelligence & Analytics Platforms Benefit: High Years to mainstream: Less than 2 Years Market Penetration: 1% to 5% of target audience Benefit: Moderate Years to mainstream: Less than 2 Years Market Penetration: 20% to 50% of target audience Benefit: Transformational Years to mainstream: 2 to 5 years Market Penetration: 1% to 5% of target audience Data Discovery – Hype CycleData Discovery – Hype Cycle Gartner also uses a 'hype cycle' to characterize the over enthusiasm of “hype” and subsequent disappoint that typically happens with the introduction of new technologies. Hype cycles also show how technologies move beyond the hype, offer practical benefits and become widely accepted and adopted. The 'benefit”' shows the degree of benefit attainable relative to a technology's progression along the Hype Cycle. It is intended as a general guide because the benefits from and maturity of any technology depend partly on industry conditions and the organization's ability to use the technology effectively. Transformational-benefit technologies change the way organizations interact with information to such a degree that they have a transformational impact on the organization's business model. For example, Smart data discovery helps organizations solve the analytical skills gap problem through the application of machine learning to assist with integrating the dataset, analyzing the variables for explanatory or predictive power, and even deciding how to visualize and present the data. High-benefit technologies are less likely to change an organization's business model, but they will have a significant impact on the organization's BI and analytics program. Enables new ways of performing horizontal or vertical processes that will result in significantly increased revenue or cost savings for an enterpris Moderate-benefit technologies such as visual data discovery, provide arguably just as much value as mentioned above. The difference is that visual data discovery technologies have been around a while and are widely expected as key parts of a BI and analytics program, which means we may be taking some of these technologies for granted.
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Corporation 11/12/15 7 7 Data Discovery – Market ShareData Discovery – Market Share 50% 8.9% • Declining BI revenues • Months to implement • IT-centric deployment • Revenues growing 78% and 17% • Days and weeks to implement • Business-centric deployment 6.2% Source: Gartner Investor Advisory Day, 9/2015 MARKET SHARE Companies are flocking to a newer breed of data-discovery tools and interactive- analysis platforms. Competitors such as Tableau and Qlik – and stealing market share away from leading BI players such as IBM , SAP and Oracle. . In fact, they're choosing these platforms even when they're not the most appropriate tools for the job at hand and despite lingering concerns about how to govern data across the enterprise. "Business-centric platforms such as Tableau Software, Qlik, and other emerging vendors have a more narrow set of capabilities, but are used more broadly for a range of BI and analytics functions -- including reporting, for which they are not optimal or scalable… -- primarily because they are easy to use and deploy," Gartner writes in its report. In contrast, companies using more conventional, IT-centric platforms (such as Cognos or BusinessObjects) that have a broad range of BI capabilities say they apply them to narrow use-cases. What's at stake in this transition is not just the survival of well-known, IT-centric tranditional, trusted BI platforms. Gartner says companies will inevitably have to reconcile why they have separate system-of-record reporting platforms and data- discovery platforms, because "no single vendor fully addresses both [needs]." Refer to Markshare analysis (Rita is warning Oracle will dispute declining BI revenues) Note, I have not listed Microsoft here as they are a bit different – growing mainly due to PowerBI. Need to refer to in voice commentary. SAS and MSTRAT in the middle and both of them are at least a bit further on Data Discovery
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Corporation 11/12/15 8 8 Data Discovery – Market Size, RevenueData Discovery – Market Size, Revenue Visual data discovery tools will grow 2.5x faster than the rest of the BI tools market. - IDC MARKET SIZING Projected to grow at a compound annual growth rate (CAGR) of 8.7% through 2018. MARKET REVENUE Qlik – $ 205 million Tibco Spotfire – $70.5 million Tableau – $38 million SAS (JMP) – $35 million Microsoft PowerPivot – $25 million. Microstrategy Visual Insight Advizor Solutions. <$ 10 million Key take-aways include the following: Gartner predicts that the market for BI platforms grew 9% in 2013, and is projected to grow at a compound annual growth rate (CAGR) of 8.7% through 2018. This makes BI platforms one of the fastest growing in all of enterprise software. Gartner found that interest in cloud based business intelligence (BI) declined slightly during 2014, to 42% compared with last year’s 45%. The report mentions that survey respondents reported they either are (28%) or are planning to deploy (14%) BI in some form of private, public or hybrid cloud. Despite this drop in the percentage of surveyed enterprises planning or actively using cloud BI platforms today, Gartner believes that this category will continue to grow as line of business (LOB) adoption increases over time. Tableau, Qlik, Microsoft MSFT +0.00%, MicroStrategy, Oracle ORCL +2.78%, IBM IBM +0.69%, Information Builders, SAS and SAP are in the leaders’ quadrant. Birst, Logi Analytics are in the Challengers quadrant, and Alteryx, Tibco Software and Panorama Software are in the Visionaries Quadrant. Niche players include Board International, DataWatch, GoodData. OpenText, Salient Management Company, Targit, Pentaho, Prognoz, Pyramid Analytics and Yellowfin. Gartner predicts that by 2017, most business users and analysts in organizations will have access to self-service tools to prepare data for analysis. Through 2016, less than 10% of self-service business intelligence initiatives will be governed sufficiently to prevent inconstancies that adversely affect the business. Gartner is seeing the majority of enterprise customers waiting to see if their enterprise-standard BI platform will deliver on the business-user-oriented capabilities they prefer to use to meet new analytics requirements beyond production reporting.
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Corporation 11/12/15 9 9 Source: Gartner Magic Quadrant for Advanced Analytics Platforms, 2014 - 2015 Data Discovery – Advanced Analytics LandscapeData Discovery – Advanced Analytics Landscape
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Corporation 11/12/15 10 10 Dashboards Smart Data Discovery Content Pre-set metrics and KPIs Best visualization Interaction Predefined Free form, Natural language Data prep IT-modelled Autodiscovery and self-service ETL Data Summary, data warehouse Big data, cloud Analysis Descriptive, some diagnostic Autodiagnostic, predictive and prescriptive Vendors Traditional, data discovery, dashboard pureplays Data Discovery - Future TrendsData Discovery - Future Trends Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms, 2015 IBM Watson Analytics
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Corporation 11/12/15 11 11 Data Discovery – Strategic approach for growthData Discovery – Strategic approach for growth
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Corporation 11/12/15 12 12 Data Discovery - Issues and challengesData Discovery - Issues and challenges Through 2016, less than 10% of self-service business intelligence initiatives will be governed sufficiently to prevent inconstancies that adversely affect the business. Opportunity to introduce AQ best practice guidance on how to evolve maturity and build a case for an analytics program (ACE). Multiple versions of the truth. Data discovery tools are regularly being sold directly to business units and business users. This is in contrast to the traditional BI sales into IT. This can lead to multiple spreadmarts springing up, and multiple versions of the truth. The flip side is that much of this can be managed and controlled if there is collaboration between the business and IT. So IT implements and manages the solution, metadata libraries & business glossaries. Opportunity to introduce AQ best practice guidance on how to evolve maturity and build a case for an analytics program (ACE). This also could open discussions up around CAO/CDO.
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Corporation 11/12/15 13 13 Ease of Use Speed to Discovery Cost of Entry Have a plan for the future 1 2 3 4 5 6 Data Discovery – Key Success FactorsData Discovery – Key Success Factors Quality of Visualization/ Interactively/ Portability Cost to incorporate future requirements
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