Data Discovery Hype

© ۲۰۱۵ IBM Corporation
Market and Competitive Overview
The Data Discovery Hype
Julie Severance
IBM Analytics Strategy & Initiatives

© 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
Data Discovery – BI & Analytics LandscapeData Discovery – BI & Analytics Landscape
Source: Gartner Magic Quadrant for Business Intelligence & Analytics Platforms 2013-2015

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
SmartVisual
Data Discovery – AttributesData Discovery – Attributes
Governed
DATA DISCOVERY

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
Data Discovery – Hype CycleData Discovery – Hype Cycle

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
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
Source: Gartner Magic Quadrant for Advanced Analytics Platforms, 2014 - 2015
Data Discovery – Advanced Analytics LandscapeData Discovery – Advanced Analytics Landscape

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
IBM Watson Analytics

11
Data Discovery – Strategic approach for growthData Discovery – Strategic approach for growth

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
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

Market and Competitive Overview
The Data Discovery Hype
Julie Severance
IBM Analytics Strategy & Initiatives

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

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.

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
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.

11/12/15 5
5
SmartVisual
Data Discovery – AttributesData Discovery – Attributes
Governed
DATA DISCOVERY
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.

11/12/15 6
6
Hype Cycle for Business Intelligence & Analytics Platforms
Benefit: High
Years to mainstream: Less than 2 Years
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
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.

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

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.

11/12/15 9
9
Source: Gartner Magic Quadrant for Advanced Analytics Platforms, 2014 - 2015
Data Discovery – Advanced Analytics LandscapeData Discovery – Advanced Analytics Landscape

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
IBM Watson Analytics

11/12/15 11
11
Data Discovery – Strategic approach for growthData Discovery – Strategic approach for growth

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.

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

11/12/15 14
14

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