
KEY TAKEAWAYS
What you
need to know
Data strategy sets the direction for how data supports business objectives, while governance establishes the controls needed to execute it responsibly.
Ownership, quality, access and security need to be defined if data is to be trusted and used consistently.
Treating governance as part of the strategy helps avoid fragmented rules and disconnected data initiatives.
In order to make the best use of your data and ensure that your business is going in the right direction, data strategy and data governance are essential tools that will help you reach your goals in a way that is cost, time, and resource effective.
To truly build a data-driven organisation which are 23 times more likely to acquire new customers as highlighted by McKinsey Global Institute, businesses have to make data governance a priority in thier data strategy.
What is data strategy?
A data strategy is a long-term plan which determines how you will use your data to create value; this plan needs to:
Define what technology is utilised
The process in place
What employees or third-party managed services are needed
The rules and requirements needed to manage the data
Your data strategy may serve several purposes, such as:
Improving processes
Maintaining data quality
Optimising acquisition channels
Reducing data storage and maintenance costs
Driving business goals
Understanding customers
Best practices for your data strategy
Defining common principles, metrics, and definitions
Support and manage the strategy across the business from C-Suite to Team Leaders
Keep track of KPIs and important metrics
Identify key challenges
Take corrective action to consistently improve data quality
Work with the right people, who understand data trends
Make use of automation where it is effective and provides value.
Mistakes to avoid in creating a data strategy
Starting with an outdated strategy
Not using your business goals and challenges as a starting point
Failing to create trackable and quantifiable KPIs or utilising sufficient metrics
Having an ineffective or non-existent approval process and chain of communication
What is data governance?
Data governance is the process of managing your data, this means the availability, usability, integrity, and security needs to be considered. You need to look at who can access what, how your internal standards are created and operated, and how the gathering, storage, processing, and disposal of data is applied across the business, as well as the operational monitoring and support processes you have in place.
Data governance best practices
Identify roles and responsibilities and ensure they are correctly assigned
Account for short, medium, and long-term governance actions
Ensure effective communication and collaboration between teams
Keep track of metrics and make sure KPIs are still appropriate
Implement compliance requirements and internal rules for data usage
Set clear and obtainable objectives
Mistakes to avoid with data governance
Seeing data governance as a one-time project
Creating a self-contained data governance team and not ensuring the process is adopted across the company
Approaching the task with insufficient tools, knowledge, or correct applications of data
Being inconsistent with data evaluation, gathering, or using inconsistent data sources
How to align your data strategy and governance
In order to align your data strategy and data governance processes, you need to ensure that you clearly define what it is that you wish to achieve (your business goals), and then identify what challenges are likely to occur, and then work towards a process that will help you in the short, medium, and long-term.
By creating a data strategy first, you can determine what you need to do, what you want to do, and where you want to take your data analytics. Then, you can create and apply a data governance process that supports achieving these goals and helps your company grow.
Ardent, helping you unlock the potential of your data
We understand that data governance is an essential part of building a robust data strategy. However, sometimes it can be the least of priorities. Therefore, we provide around-the-clock (24*7) operational monitoring and support services to keep your data in check, ensure it meets your security measures and more. Discover how our clients are succeeding with our excellent data engineering services:
Making data science efficient with expert operational monitoring and support services
Monetizing broadcasting data with trusted and timely data availability for real time, mission critical data
If you are looking to have your data handled by experts, with a proven track record of success and experience, we can help. Our highly skilled data engineering teams are proficient in world-leading technologies and can help you achieve your data goals.
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