What gets measured, gets managed; but what gets governed, generates real value. That's one major reason why data governance has risen to a top priority for most organizations. Another reason is the rapid onboarding of big data, which often comes from beyond the traditional firewall. And then there are the authorities: issues like privacy, security and fiduciary responsibility are combining to make data governance a must-have. Register for this episode of The Briefing Room to hear veteran Analyst Dr. Robin Bloor explain why governance should be viewed as a positive change agent for the modern enterprise. He'll be briefed by Ron Huizenga of IDERA, who will discuss a practical, model-based approach to enterprise data governance, with a focus on Master Data Management.
25. Big Data Means Big Governance
The analytical opportunity of BIG
DATA is clear – there are already many
profitable uses
Nevertheless, all data needs to be
GOVERNED
26. The Data Governance Challenge
Data Sources
Metadata Management
Data meaning
Data compliance
Data provenance & lineage
Data cleansing
Data security
Data audit record
Data life-cycle mgt
Data Governance is a perpetual
process
27. The Growth of Compliance
u International
– GRC (Governance, Risk,
Compliance)
– ISO (standards)
u US Government:
– SOX
– GLBA
– HIPAA
– FISMA
– FERPA
u Europe
– GDPR (Data protection laws)
with variances
– New: The right to be forgotten
28. The Full Data Lake Picture
Data
Cleansing
Data
Security
Ingest
Metadata
Mgt
Real-Time
Apps
Transform &
Aggregate
Search &
Query
BI, Visual'n
& Analytics
Other
Apps
Data Lake
Mgt
Data
Governance
DATA LAKE
To
Databases
Data Marts
Other Apps
Archive
Life Cycle
Mgt Extracts
Servers, Desktops, Mobile, Network Devices, Embedded
Chips, RFID, IoT, The Cloud, Oses, VMs, Log Files, Sys
Mgt Apps, ESBs, Web Services, SaaS, Business Apps,
Office Apps, BI Apps, Workflow, Data Streams, Social...
30. Points To Note
u The more complex the
data universe the more
you need a model.
u In theory it is a view of
the data universe. In
practice it is part of it.
u Beginning: Modeling is
top-down and bottom
up. You build in both
directions
u It is not and never can
be a project. It is an on-
going activity.
31. The Net Net
Because IT and data management is
evolving so quickly, governance and
data modeling must also evolve
quickly
32. u Agile modeling clearly requires effective
collaboration between all data users at every
level. How does your technology help with
cultural issues?
u Which data stores and databases do you
support aside form the usual relational
sources? (Hadoop, NoSQL, unstructured,
etc.)offer for NoSQL databases?
u How do you accommodate the IoT?
33. u If you do not do MDM already, how do you start
and what are the immediate business benefits?
u Do you model data flows (consider, for example,
real-time analytics)?
u Where do you see current/future competition
emerging from in the modeling or governance
market?