Data governance involves setting up procedures and regulations to enable the smooth sharing, managing, and availability of data.
The idea is to prevent an overlap of resources. When you have data governance procedures you experience faster decision-making processes while moving data from just a company’s by-product to a critical asset within the organization. Check out this and know how to build a strong Governance framework for your organization
2. DataLumin WHAT IS DATA GOVERNANCE
• Definition of a company’s assets has changed over the years
• Transformed from physical buildings to virtual assets like data & intellectual property
• Increased sharing of company data necessitates companies to develop solid framework of regulations to regulate
how data is handled, managed, and processed
4. DataLumin DATA GOVERNANCE STRATEGY
Defines how data is named, stored, processed, and
shared. Instead of data being a by-product of your
applications, it becomes a vital company asset. The
strategy defines how data will be used efficiently in an
organization.
Eliminates duplication of resources while enabling
access to vital data by those who need it in an
organization
Effective data governance strategy can tell you where
data originates from, where it is stored, and who can
access it
Precedes & boosts regulatory compliance
5. DataLumin COMPONENTS OF DATA GOVERNANCE STRATEGY
STORAGE
IDENTIFICATION PROVISIONING
PROCESSING
GOVERNANCE
6. DataLumin COMPONENTS OF DATA GOVERNANCE STRATEGY
IDENTIFICATION
• Identify the origin of the data
• Proceed to cleaning, manipulation and storage
• Just like you identify residential houses through postal addresses,
your data has to be well catalogued
• In this regards, the data will have a name, a value, defined format,
and source
7. DataLumin COMPONENTS OF DATA GOVERNANCE STRATEGY
STORAGE
• More than physical storage but encompasses the ease to share various data streams
across the organization
• Understand and document the overlap as to who gets to use the raw data
• Allocate storage space depending on the type of data being processed – analytical
systems, transactional processing applications or general purpose files
• Plan how this data will be moved between the various organizational systems
• Efficient storage strategy will help users access data without the need of copying it
8. DataLumin COMPONENTS OF DATA GOVERNANCE STRATEGY
PROVISIONING
• Data reuse and sharing has become the norm in the modern world
• This necessitates data strategy provisions to decode this data so that it can be used by
another part of the organization
• Instead of data being decoded to serve specific applications it should be done with the
user in mind
• Sharing of data helps the company to increase their productivity will boosting
operational efficiencies
9. DataLumin COMPONENTS OF DATA GOVERNANCE STRATEGY
PROCESSING
• For Data to be useful, it has to go through a process of preparations and
transformation so that it conforms to a wide range sources within the organization
• Developers will be responsible for the task of standardizing and transforming this data
for use by various end-users
• Aim of process is to ensure that data can be reused and shared
10. DataLumin COMPONENTS OF DATA GOVERNANCE STRATEGY
GOVERNANCE
• Need to have a set of regulations to govern how data is handled by applications and
staff members
• Once policies are in place, they will lay out what to do during data naming, sharing and
manipulation
• While developing a governance structure you should ensure that it is not rigorous and
complex
• When data is able to flow to all the organizations constituents, it has the added benefit
of boosting productivity
11. DataLumin BENEFITS OF DATA GOVERNANCE
Operational Efficiency
We live in a data driven world and companies are finally coming to terms that
their data is part of the company’s asset. Instead of data being held by one
party, data governance strategies enable the efficient sharing of data
Boosts Collaboration
When data is open to everyone needs it in the organization, it boosts
transparency and collaboration between teams in the organization
Keeps Data clean
Many organizations spend a lot of time accumulating data.
Having a data governance strategy, ensures that the data you
are storing is clean. The data will need to be updated or
deleted for it to be relevant
12. DataLumin BUILDING A DATA GOVERNANCE FRAMEWORK
Policies
& Standards
Information
Quality
Privacy,
Compliance
& Security
Architecture
Integration
Establish
Decision
Rights
Stewardship
Access Risk &
Define
Controls
Consistent
Data
Definitions
Technology & People
Data Literacy
Data-Driven Improvements
ChangeManagement
13. DataLumin BUILDING USER STEWARDSHIP WITHIN GOVERNANCE FRAMEWORK
DATA
GOVERNANCE
COUNCIL
DATA TRUSTEE1
DATA STEWARD1
DATA STEWARD2
DATA STEWARD3
DATA TRUSTEE2
DATA STEWARD4
DATA STEWARD5
DATA TRUSTEE3
DATA STEWARD6
DATA STEWARD7
Data Governance Council
Primary function of the Data Governance Council is to provide ongoing
management and oversight.
Council manages
• Data governance initiatives
• Issues, and escalations to improve and promote
• Data Quality and Integrity
• Appropriate and ethical use of data
• Compliance
• Data Literacy and Awareness
Data Trustees
Those with authority over source Data systems. Data Trustees are accountable for
managing, protecting, and ensuring the integrity and usefulness of Data and for
upholding policies, system policies, state and union law. Each Data Trustee appoints
one or more Data Stewards for the Data Trustee’s specific Data Domain
Data Stewards
Data Stewards help define, implement, and enforce data management policies and
procedures within their specific Data Domain. A Data Trustee may delegate to the
Data Steward the authority to represent the Data Trustee in data-related policy
discussions
14. DataLumin KEY RESPONSIBILITIES OF DATA STEWARDS
Data Stewards
Data Stewards are the first line of defence and core
implementers of policies. Their major responsibilities
include
• Identifying major data systems where data under the
Data Steward’s responsibility resides
• Classifying & cataloging data systems according
to Data Classification policy, working with security,
privacy officers, and review classifications at least
annually
• Building relevant reports, analyses and dashboards for
the functional areas that they are responsible for
• Classifying reports and dashboards that deliver or
expose data for which the Data Steward is responsible
• Reviewing and approving requests for access to Data
Sample framework
Data
Domain
Applications Data
Trustee
Data
Steward
Steward
Area(s)
Major Data
Systems
Marketing Campaign
Effectiveness
Krishna Bhavna BTL
ATL
Hubspot
Marketo
Sales Sales 360 Aasma Abhijeet Sales SFDC
Ops Interlock Aasma Pravin Sales Ops SFDC
ServiceNow
Information
Technology
Asset
Management
Sudhir Mary IT &
Cybersecurity
ServiceNow
Splunk
16. DataLumin
DataLumin.
ATeam that worked in Big 4 Consulting
Organizations andWorld-Class Software Companies
coming together to provide customers with the best
Data experience
17. DataLumin
WHAT WE SPECIALIZE IN
CREATING RIGHT
PLATFORMS
BUILDING RIGHT
MODELS
ENGINEERING RIGHT DATA
STRUCTURES
FORUMULATING
RIGHT DATA
STRATEGY
18. DataLumin WHAT WE SPECIALIZE IN
INSIGHT SCIENCE
DATA SCIENCE
DATA ENGINEERING
ADVISORY
DATA INTEGRATION
BIG DATA MANAGEMENT
DW & DL AUTOMATION
DATA MIGRATION
DATAVISUALIZATION
CONVERSATIONALAI
DATA LITERACY
MACHINE LEARNING
TEXTANALYTICS & NLP
ANALYTICS BLUEPRINT
DEPLOYMENT FRAMEWORK
ADOPTION SERVICES
INDUSTRY SOLUTION DESIGN
COE DESIGN
20. DataLumin
DATA & ANALYTICS CHANGING HOW COMPANIES COMPETE
70% of all Executives report that data and analytics have caused at least moderate changes in their industries’
competitive landscapes in recent years
8%
26%
36%
21%
7%
2%
Fundamental Change
Significant Change
Moderate Change
Minimal Change
No Change
Don’t Know
New entrants launch data-and-analytics businesses that undermine traditional competitors’ value propositions
Traditional competitors gain an edge by improving core business through data and analytics
Companies extract new insights from data that were traditionally unrelated or in different systems
Traditional competitors are launching new products, including analytics services
Companies are forming data-related partnerships along value chain
Traditional competitors are launching new data-and-analytics-related businesses
Traditional competitors are pooling their data into a shared utility
50
36
36
27
21
18
7McKinsey CxO Survey
21. DataLumin
5 KEY PILLARS TO UNLOCK VALUE & STAY AHEAD
Aligned Analytics & Strategy
Have a clearly articulated vision and
strategy that aligns capabilities with
business needs and promotes
transparency across functions
Flexible Organization &
Operating Model
Reconfigure an organizational and
operating model to best support
demand for analytics
Empowered Analytics &
Governance
Design a holistic governance model
that establishes clear ownership and
accountability for data
Innovative Talent Strategies
Develop innovative processes and
partnerships to recruit, retain and
grow in-house talent
Modern Technology Platforms
Invest wisely in new technology to
enable self-service analytics across
the business
22. DataLumin
DATALUMINADDRESSESTHESEAREAS
To ensure your information workers
a. Get Trusted Data
b. Explore freely & make sense of the data
c. Derive insights, collaborate and multiply
that effect
To help you cut through
clutter, work with best-in-
classTech and get
maximum value for the
investment
23. DataLumin ONE WAY TO MOVE FORWARD
01
TO BE STATE:
Study of
Objectives at
• Organizational
Level
• Department
Level
03
Derive theGaps
that need to be
addressed to
get to theTO-
BE state
05
Re-assemble
and choose the
right path
where can start
the work
02
AS-IS study of
current Data
Processes
04
Offer multiple
paths to get to
theTO-BE state
with cost-
benefit analysis
of each path
Policies and Standards: The program will determine who has the authority to make decisions regarding access, priorities, and data usage standards, and under what conditions those decisions can be made.
Information Quality: Formal and professional data stewardship is an essential part of any data governance program. Those responsible for data stewardship are accountable for the integrity and quality of our data.
Privacy, Compliance, and Security: How we institutionally deal with the inherent risk that comes along with curating data is an essential part of the program. The program will develop the risk management
strategies and identify ways to operationalize those strategies. Additionally, the program should align with and coordinate with records management custodians to ensure compliance with applicable requirements.
Architecture and Integration: Ensuring that there are common data definitions and that those definitions are made available across platforms is essential to enabling informed data-driven decision-making. The program will make decisions on what those definitions are and how we technically support the requirements of those definitions.
Guiding Principles
Transparency: It should be clear how and when decisions are made and processes are created.
Metrics-Driven: We should measure and report on how we are doing against our goals.
Consistency: All decisions should be applied consistently.
Stewardship: While there will be formal stewardship roles defined, it is everyone’s responsibility to protect the privacy, security, and confidentiality of our data as required.
Accountability: Decisions and processes should be audited.
Agility: All processes should be able to adapt when appropriate.
Change Management: New processes will require a concerted effort in managing change
DataLumin exists for a reason. We solve the fundamental data problems. To provide the best experience in the data world to ensure customers harness the power behind utilizing the data they possess and need to transform their organization. When people place data at the center of digital transformation, they invariable are at a leap’s distance from competition. That is our Motto - to give customers the best data Experience!
As DataLumin, we solve all the data problems after you have collected it. We help formulate the right data strategy for you. We help in engineering the right structures that hold your data for easy consumption. We work with ML & AI tech to build the models that uncover the insights. We create the right platforms for you not just to visualize but converse with your data and get the hidden insights that can potentially change how you look at data. We also help your organization become data literate to maximize the time investment people make in working with data day-in and day-out
And that problem-solving ability is what you can see in what we specialize in. There are 4 pillars we work on. The advisory piece - to create an Analytics Blueprint, a strategy document that talks about what kind of a journey you will need to take given your landscape (both tech and people). A detailed deployment framework that talks about what deployment strategy to undertake and what does it take to create those governance mechanisms to ensure a smooth and successful deployment. Adoption services that create a short, medium and long-term plan that will ensure that the organizations becomes data-driven. Industry specific solution design that gets you the right metrics across different functions from our ever-updated industry repository. And Finally, building a Center of Excellence and this is of particular importance when you are a multi-geo organization and when you have to create an Ops center that will scale with the data needs of your organization.
There are many ways! But the first step is what we call a Phase Zero.
In this, we take the following steps