5 Steps in implementing a successful Data Governance strategy

 For today’s contemporary IT systems, good quality data is essential to bring value to users, irrespective of the department let it be finance, supply chain, operations, or even HR. But one thing all the users and the data team know is that data doesn’t format itself or even tell you how it can be used. 

Data just exists. It is up to the users to find insights and change data as per their requirements. So, for this to happen, and to maintain its integrity, availability, and usability, all organizations need a Data Governance strategy. 

What is Data Governance?

Data Governance involves managing all the aspects of the data of an enterprise. It involves setting up all the procedures, regulations, policies, and internal data standards which are based on the company’s organizational strategy to establish the data requirements and designs. Data Governance is not an ad-hoc attempt but needs to be based on the company’s vision, strategies, business rules, standards, and capabilities to manage the data. 

Overall it is to have clean, usable, accurate, and secure data for all the users in the organization. But if you’re thinking about whether your firm needs a Data Governance strategy, keep reading.

Reason 1: Data Availability

With the increasing trend to store and utilize unstructured and semi-structured data from different sources in non-relational databases or data lakes, it is not possible to know beforehand the data that is acquired and what to make sense of it. 

But having to store and analyze all the data irrespective of the needs of the user would be a waste of space, time, and money. So, Data  Governance starts by identifying what data to capture, and what different departments need, rather than storing and analyzing everything under the sun

.

Also Read | 5 Elements of Data Strategy

 

Also, it is important to ensure that the data is being available across the organization as per their requirements with their security levels intact. Even for Self-service BI tools, advanced analytics, and other requirements you might think for the usage of data, you need the data to be present primarily, which requires database handling.

Reason 2: Improved Communication and Collaboration

The utmost sin that can be done by a company internally is having Data Siloes. We are not talking about various department owning their own data, but about having a uniform data governance process across the organization, with such a practice you can have improved communication. 

All the individual departments can have their needs, priorities, and constraints applied at the core level and distributed across.

Also with a unified governance approach, data can have consistency and reliability. Two different departments can use the same data to find different insights, for example, Sales Data can be used by the Marketing team to identify the most valuable consumer with analyses like RFM, whereas the same data can be used by the Financial team to analyze regional or nation-wide P&L. 

So, even though there might be multiple departments that might use the same data, providing the data to the departments should be a unified approach to maintain collaboration.

Reason 3: Prevention of Data Swamps

You might normally find the word “Data Swamps” as a downside of improperly managed Data Lakes. But let’s face the reality once. All organizations need data from various sources, some unstructured, others are semi-structured and structured. But how much of these do you need? 

For example, if you are trying to perform Sentiment Analysis for your organization with Social Media data, would data 5 years ago be relevant for you? Probably not. 

Similarly, you need to determine which data to keep and which data to delete consistently at a regular time frame. IT servers and storage units that are full of useless junk make it hard to locate any data of value or to do anything useful with it later. 

For example, even Walmart uses only the last four weeks’ transactional data for its daily merchandising analytics. So, think about what is the data that you want and what you don’t.

These are our three main reasons, but there can be an insane amount of reasons as to why a company should need a Data Governance Strategy. It would help with resolving analysis and reporting issues. 

This will also increase the adoption rates of technologies by the people and stop blaming the technology in case something happens. With a proper strategy, Security and compliance with laws and regulations can be made accessible and understandable throughout the organization.

5 Components in an effective Data Governance strategy

We have seen why Data Governance is essential for any organization. Let’s also look at a few steps in identifying a framework for having data access across. 

 

• Identification

We have discussed above how organizations have found the need to use data from various sources. Before the analysis is performed, there is a need to identify the origin of the data. By identification, we mean the type of the data, the cleansing and manipulation it needs, and the mapping of the data to the end-user departments.

• Storage

Data storage has become cheaper than it was in the last decade. With service providers Snowflake, AWS, Google Cloud, S3, Azure, etc., organizations have the capability to store, compute, and analyze data as per your needs and future requirements.  

• Provision

We have come a long way from having to store servers on-premise and occupying physical and virtual servers space. Now, with organizations growing increasingly digital you can have a hybrid or a completely virtual mode of data storage all the while ensuring security. 

You can utilize applications to pass on the data directly to various organizations instead of making a copy and having multiple replicas of the same data reducing server wastage.

• Process 

Data in raw format is of little use to people other than Data scientists. So pre-processing the data to make it user-friendly, easy to digest, and readable is important. 

With data governance, the IT department or the ones responsible can have a standard procedure to standardize and transform the data as per end-user requirements

• Govern

It sounds like the excel circular formula to have the same cell referred to in its formula. But what we mean by governing here is the establishment of a set of regulations to identify processes about how data is being handled by the departments and for other applications. 

Though making rules is easy it all boils down to the execution and the adoption of the governing rules.

Conclusion

If you want data to be your asset, Data governance becomes more of a necessity, which will be further helpful in identifying trends, patterns, and hidden truths behind your data. But Effective data governance is also a continuous process. 

Compliance reviews, Quality assurance & control, Policies recheck, etc., are essential to have an effective data governance life cycle. It would ultimately be helpful in generating business insights correctly and take sound business decisions.

Are you looking for Competent Data Analysts for your business in USA?

Hire Polestar Solutions & Services!