The document discusses trends in data management and governance. It notes that data quality is decreasing each year while data sources and types are increasing. Many organizations still view data as a byproduct rather than an asset. While regulatory requirements are driving some data cleansing efforts, master data management is still immature in Israel. As business intelligence becomes easier to use, effective data management and governance are becoming more difficult. The role of the business user is growing, while IT will focus more on data quality, access, and channels to analytics tools. Most organizations have a long way to go to reach a mature level of data governance.

1. Einat Shimoni
Enterprise
applications
Data management & data governance trends

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Data governance: the elephant in the room
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Quality of data decreasing each year by 10%
Number of data sources and data type increasing
Data perceived as a by-product of transactions, not as an asset (what is
the cost of inaccurate data?)
Mature technological tools. Israeli market is picking up but still not
mature in all areas:
Regulations in financial/insurance market -> data cleansing
MDM is NOT yet mature enough in Israel!
CDI was the main MDM focus but lately also PIM - Financial products
management (banking / insurance)
Data quality as part of a migration process (usually one-time, not continuous)
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The Technological (and political) Problems
Legacy data sets are modeled with vertical applications in
mind, which leads to the duplication of the same information
across multiple data sets
Creating one “single version of the truth” (source of
information) isn’t enough, you have to control the way end
users extract and use it
Organizations with vertically structured IT organizations may
not be "politically" ready for the move toward a centralized
representation of customer information

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How do BI trends impact EIM?
BI is becoming easier, data management is becoming harder
Data explosion will drive the need for data quality
Self service BI will drive the need for data governance
Loss of central control. The BI user will be “the boss”
Big data = bigger data quality problems
IT should establish a central COE and data governance
BICC will return as best practice
Data management is not a project, it’s an ongoing program
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Analytics & BI Generations
Gen. 3:
Active Analytics
End user is boss
Classic DW model
DW updated
frequently
Proactive BI
DW updated once
a day
Static Reports
Gen. 1:
Passive BI
IT is the boss
Real time
analysis of data
“on the move”
BI insights linked to
operational processes
Gen. 2:
Active BI
IT is the boss
Usage of data
mining tools to
create new
insights
We are here
Gen. 4:
Big data analytics
End user is boss
Distributed data
model
Predictive analytics
Structured data Unstructured data
Passive BI
Advanced
visualization
Self service
Use of in-memory
Structured data Structured data
DW updated
frequently
Central data approach
Central data approach
Interactive
analysis

7. BI State of the Market: Major changes ahead
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One of the most adopted technologies (after ERP) - 68% of large
organizations (Source: Computer Economics)
But still one of the most innovative areas
Next few years will focus on analytics, self service, visualization
What about big data?
Big data will “meet” these trends and empower them
Will be an enabler for new type of analytic solutions
Data explosion – too much data!
Einat Shimoni’s work
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The natural evolution
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 The top performers (“high digital IQ”) will lead the way into big
data, and they are preparing for it
Source: http://www.forbes.com/sites/davefeinleib/2012/07/24/big-data-trends/
Source: PWC Digital IQ survey

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Big Data in Israel?
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Yes
23%
No
77%
My organization will enter into a
big data project
Source: STKI Survey 2013

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We now create as much information every two days as we did
from the dawn of civilization to 2003 (Source: IBM CMO Study)
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Top 3 concerns:
• Data explosion
• Social media
• Growth of channel & device options
Source: IBM CMO study

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To small data
From Big Data
Small data = the new big data

12. Too much focus on “big”
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Big data is less relevant, right data is most
important: how to get the right data in real time?
It’s what you do with the data that makes the
difference
The challenge :convert data into actionable info.
Data Scientists will play the most important role
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13. MEGA Trend – BI ownership is shifting
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IT will focus on data quality and access + effective channels to BI
Business users will be the owners of BI and analytics
By 2014, 40% of BI purchasing will be business-led (Gartner)
Benefits: operational efficiency for IT (reporting and analysis
done by LOBs), agility, usability, relevance, fast deployment
The price: consistency, integration, central control
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14. Roles and organization of the BI department will change
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Less people creating reports at the BI department
More BI will be done in LOBs by analysts / key users and hopefully new types
of users – knowledge workers (self service)
BI department will focus on:
Data governance, central definitions and models
Data quality issues
Center of Excellence for guiding users
Creating effective channels to access the data
 Search based BI portal
Visualization tools
Self service
Data discovery
Einat Shimoni’s work
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Data governance maturity model
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By-product of
transactions
No synch
Data siloes
Tactical
IT driven
ODS
Process-
focus
Business
involvement
Data = asset
Business leads
Source: http://blog.kalido.com/road-data-governance-maturity/
Data management Data governance

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Worldwide maturity level
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Source: http://blog.kalido.com/road-data-governance-maturity/
64%
0.5%
13%
22.5%

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Perception gap
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