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Out of the Data Lake and Onto the Platform

In Software & Cloud Economics

Optimising data governance in an increasingly AI-centric world

Artificial intelligence (AI) is no longer the stuff of science fiction but is being applied to helping businesses gain a real competitive advantage.

Advancements in AI have been the result of innovations through the massive volumes of data currently available and, more importantly, using machine learning (ML) algorithms to crunch through this.

Gaining a business advantage using artificial intelligence and machine learning requires well-understood, well-organised and trusted data. According to analysts at Gartner, artificial intelligence will generate $1.2tn worth of “business value” worldwide in 2018. It added that this amounts to a 70 per cent increase over 2017. It also states AI will be adding $3.9tn by 2022. Its forecast: The business value of artificial intelligence, worldwide, 2017-2025, report, said that three sources of “business value” were customer experience, new revenue and cost reduction.


Diving into a data lake

In the past, businesses have used data lakes. These centralised repositories allow enterprises to store all their data (structure, semi-structured and unstructured), including raw copies of source system data and transformed data used for tasks such as reporting, analytics and machine learning.

This term is most often associated with Hadoop-oriented object storage. Data is downloaded onto a Hadoop platform and then business analytics and data mining algorithms are applied to datasets. There is no hierarchy or organisation among the individual pieces of data in a lake, it is unprocessed.

When it comes to processing this multi-formed data, normal data analytics just isn’t enough. It requires artificial intelligence and machine learning to quickly process this to figure out and find the insights that business needs.

And while AI will transform the way enterprises gather, analyse and eventually benefit from data, there are parts of analytics that will be required for AI’s success, principally as it relates to data governance.


Putting data governance into AI-based analytics

As a quick reminder, data governance refers to the processes which ensure that an enterprise’s master data is properly managed.

With massive amounts of disparate and diverse data coming into the enterprise it is essential for organisations to have an effective data governance strategy in place in order maximise the potential of not only the data it has but also the potential of AI. This strategy requires that the fundamentals are in place.


Back to basics

To have an effective data governance strategy in place that can realise the full potential of AI, enterprises must start by looking at what information assets are the most important to achieving its goals and objectives.

An enterprise’s leaders need to determine the priorities for the data most useful to managing operations and driving strategy.  According to Gartner’s third annual chief data officer (CDO) survey, the CDO is set to become a key position in business.


Encourage a culture driven by knowledge

It’s the daily implementation of effective data governance that leads to results, so it’s important that your enterprise gets up to speed quickly. Those members of staff better equipped in applying governance practices should be teamed with those lower down on the learning curve too.


Break out of those silos

We all know that there are informational and organisation silos in a lot of enterprises, so ensure that once one part of the organisation has gained a good grounding in governance, this experience and knowledge is shared with other parts of the enterprise. This can help in building up a good comprehension of what data they can use, what it means and how it can help them make better decisions.

The next few years will be crucial to how AI impacts organisations in ways we cannot comprehend at present. But this does mean that the basics provided by traditional data analytics will be more essential than ever before.

Fortunately, good data governance makes data more accurate and dependable allowing artificial intelligence to reach its full potential and businesses to gain a competitive edge over slower, less data-driven rivals.

To find out how you can optimise your data governance strategy and use AI to business advantage, please visit: