Data Governance: It’s a jungle out there!

The value of data and how to create more value with it is a major challenge today for decision-makers with the emergence and democratization of “big data”. Numerous companies have recently embraced a data-driven operational and strategic decision-making process, and data is now considered to be an asset with a high potential value.

However, the paradigm shift toward a reliance on the use of big data has required companies to start thinking about how they will deal with a new challenge: data governance. This almost mystical revolutionary concept is one of the biggest challenges that companies will face in the years ahead as they dive into the troubled waters of the “data lake”, with data governance fast becoming the best lifeline asset with which to navigate them.

Our Montréal data analytics experts demystify data governance by answering questions the companies most frequently asked.

In the context of the changing data landscape brought on by big data, what will the impacts on data governance be?

With the advent and emergence of big data, and given companies’ increasing reliance on it, we note that the sheer volume of data is increasing exponentially year on year. The new and changing ways of accessing data – and data’s power as a tool – require us to look anew at the issue of governance. Data is being utilized in more innovative and dynamic ways, resulting in an increase in data frequency with a corresponding diametrically opposed demand for decreased latency. Governance has to be similarly flexible whilst also process-driven in order to avoid becoming a bottleneck in the big data pipeline. Moreover, understanding and profiling data is critical to the data governance process. This way, you can ensure that you are using the right data and that you don’t turn the power of data against yourself.

What are the main risks of not having proper data governance?

In the initiatory journey through the data analytics wilderness, as it were, there are four main risks for companies who currently operate with a lack or absence of data governance.

First of all, companies can easily end up with a big “data swamp” instead of a so called “data lake”. In this scenario, users suffer from a combination of information overload and insufficient metadata.

Second, companies can be penalized by data protection and privacy legislation that requires companies to have strong data governance, traceability and privacy controls such as masquerading. The number of rules and regulations over data privacy and protection are rapidly increasing as access to data is democratizing and the amount of information available is growing. Just one example of recently passed legislation is the 2016 General Data Privacy Regulation enacted by the European Union.

Third, as a company needs to ensure the integrity of its data, poor data governance can compromise any strategies which have been built based on data analytics. This can result in making poor decisions, and it can ultimately lead to a financial and reputational risk for the company.

Last but not least, poor data governance can also result organizations experiencing difficulties dealing with and adapting to technological change.

In addition to the four significant risks related to a lack of or insufficient data governance, we have observed that many companies are facing major challenges when it comes to safely navigating the “data lake”. And this particularly true of companies who have not placed sufficient importance on their data governance structure.

What are the main challenges for companies that have not implemented data governance?

Companies now facing some major challenges with their data strategies have hit a wall and have failed to achieve the purported benefits of big data due to the “data swamp” effect. Most of these companies struggle to utilize existing data assets effectively to achieve their strategic goals. This is very often due to low data scientist productivity, where significant time is spent obtaining, validating, cleaning and transforming data. Our team of experts can help companies get over the wall and get more value from their data.

Whether your company needs to improve the usage of third party data assets (e.g. demographics, segmentation, customer information), develop the potential of poorly rationalized and under-utilized information, or obtain assurance over the quality of its data and ensure its integrity, we have the relevant expertise to help you face your biggest challenge.

Is the process of implementing data governance long, painful and expensive?

If you come to data governance later on in your journey through the data analytics wilderness, then the answer will likely be “yes”. But it doesn’t have to be if you are value-driven (i.e. driven by business priorities and needs and not by IT mandates) and if you adopt an agile implementation approach where the full benefits of governance are realized piecemeal by various cross-sectional groups.

When is the best time to implement a data governance plan?

Based on what we have discussed above, you will agree that yesterday is a good timing.

What is the return on investment a company can expect?

The return on investment that a company can expect is both from an operational perspective and a management perspective. A sound data governance plan will bring a company greater synergy between its services and will help it consolidate its analytic methodologies, thus allowing it to reach its goals.

Data governance will lead to higher management productivity due to more efficient and effective provisioning of performance data, and due to rapid evidence-based decision-making that will come as a result of higher data reliability (trust).

Data governance will allow a company to lower its IT costs by a substantial margin depending on the replacement of dimensionally modelled RDBMS and OLAP solutions (data warehouses and data marts) with a tightly coupled “big data” platform.

Data governance will support a company’s efforts to generate higher revenues because the company will be using data assets more efficiently. An example of this would be higher customer satisfaction through the capitalization of real-time data streams (customer transactions, online sentiment, etc.).

In general, companies will be able to reap many other benefits from enhanced data science productivity.

Could you share the leading practices you see in the market regarding data governance?

Based on our experience with companies that have gone through the process of implementing a data governance plan, we have noted the importance of the integration of data platforms (i.e. Hortonworks, Cloudera, Microsoft HDInsight, etc.) and data governance toolsets. This has led to successful integration processes and timely operational effectiveness. Moreover, most of the companies we have seen successfully transition to a governed data environment have implemented a process-driven governance plan with no “orphan” end states (i.e. if data isn’t actively used and governed to a minimum standard, it gets automatically purged).

Swamped by an excess of data? Need to master your data to reach your goals and create value? Our team of experts can help you better control your computing environment by implementing a successful data governance plan. To learn more about PwC’s data analytics solutions and about how we can help your organization harness its "big data” potential, please contact Ramy Sedra.


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