Many businesses have encountered disruptions due to data privacy legislation like GDPR and CCPA. For example, many firms were not in compliance when GDPR came into effect, and some did not even know where to start.
Things do not end with disruptions caused by GDPR. Problems related to data governance will become more intense with the advent of CCPA in California and the prospects of actuating the national consumer data privacy rules for the U.S.
But, many businesses are yet to know how to go about it. And most of them are clueless about how data moves through an organization, how to modify data and where to store data. At the same time, some businesses are acquainted with spreadsheets in storing and managing data. But, unfortunately, spreadsheets are susceptible to human error.
Data governance can have positive implications for your business.
Let us go through the following five reasons to discover why you should map your data using automation:
Compliance
It does not matter whether businesses like it or not. Data privacy laws are here to stay. And GDPR came as a surprise to companies.
What makes things difficult for businesses in achieving compliance with GDPR and CCPA. First, companies should know how data comes in, where it goes, and it gets transformed.
The difficulty arises due to the absence of a data path map in their business environment. In this context, bear in mind that spreadsheets are not a solution.
What you need is accurate and centralized documentation mapping your data. And automated tools to speed up the process of actuating foolproof compliance.
Time Efficiency
Despite data scientists bringing significant value to a business due to their specialized skills, they have to spend 30 to 40 per cent of their time doing data preparation instead of analysis. In addition, they spend valuable time on basic tasks, such as determining the data sources.
When data scientists waste time doing the basic tasks, the business loses valuable time and opportunities that could be derived if data scientists spend time on productive work, such as data modelling, actionable insights, and predictive analysis.
It will help if businesses automate such basic tasks to increase the productivity of data scientists.
Speeds-Up Data Transition
Many businesses move data from their in-house data centres to cloud databases, which is a cost-effective solution. It is an efficient way to modernize your data infrastructure while saving costs. But you should know the data that flows into your on-premises hardware. Or else, you will not be able to point the same pathways at the cloud.
But it will be a time-consuming task to document the pathways manually. Therefore, it will help if you use automation to map the data pathways to speed up the transition.
Eases Communication
IT and business often find themselves uncooperative. And it is one of the factors that many companies have fallen behind in mapping their data.
Consider the typical ETL coders. They go by codes. Suppose you ask them about data mapping. They are likely to answer that it is in the code. They tend to prioritize code over everything, not to mention documentation. It often creates miscommunication within a business.
There arise two perspectives. While business users find IT team members uncooperative, IT team members can view business users as demanding.
But, you can turn the contention into values using the right tools, with which businesses can create glossaries that relate business terms to technical metadata. Ensure that the glossary contains every term associated with GDPR.
With such a glossary, there can be better communication between the IT team and business users.
Making Right Decisions
Data mapping is essential. Without data mapping, you cannot know the data sources and how it was modified.
If you do not know the data sources, you cannot figure out whether it is accurate and fit for decision making. You cannot trust any insights generated from inaccurate data.
You should ensure that your business data is accurate and high in quality so that any decisions based on the data can be precise and accurate.
Conclusion
With the data privacy laws, you cannot escape from knowing the entire path through which data flows through your business. It also helps to map the data. But, manual processes are not efficient, and that is why you should use automated tools. Data governance has become crucial, and you should implement it if you are yet to implement it.
