While many organisations are realising the benefits that artificial intelligence (AI) has to offer, for those who have yet to take the plunge, simply knowing where to start on their path to digital transformation can be a real challenge in itself. In particular, companies who want to use AI to gather new insights from their data must first have in place a solid data strategy.

Given the large volume of data typically gathered and processed by today’s businesses, creating a strategy that will harness all that information in a clear and useful manner can seem virtually impossible. Where do you start? What exactly are you looking to achieve?

The following tips will help organisations of all sizes create a data strategy that will set them on the best path to using AI to gather business insights from their data:

1. Identify where data is stored – and how

Data is likely to be stored in all kinds of formats, from emails and documents to structured databases, and across various locations and standalone databases. Without a clear overview of their data, businesses could be missing out on all kinds of opportunities, from coordinating promotions to ordering stock in response to patterns of customer demand at different times of year.

2. Keep it in one place

Which brings me to my next point: all data should be kept within a centralised data lake to make it easily accessible.

A cloud-based service is an ideal place to start, as they are usually far less expensive than an on-site data centre. Ideally, organisations of all sizes should choose a platform that is easy to scale – in both capacity and performance – and think about which format they need their data to be available in. Using a translation tool such as Kafka will make it easier for companies to manage data from different apps.

However, with so much important information held together in one place, the issue of security becomes more important than ever. A solid backup and recovery plan is a vital element of any data strategy.

3. Cleanse all data

It may sound obvious, but companies should always dispose of data that’s no longer used or of value to them. This is particularly important when meeting GDPR regulations too. Most companies have decades-old data, often customer orders or a contact at a business that no longer exists. Finding this data and destroying it appropriately is critical to being able to manage all your relevant data effectively. 

4. Ask the right questions

Once an organisation has achieved the task of gathering, cleansing and storing its data in one place, it’s time to think about the questions that need to be asked of the data. This means understanding and looking for the insights that will make the biggest difference to your business.

With a set of objectives in place, it’s worth testing these with a smaller data set to reveal whether you are asking the right questions – and whether the right algorithms are being used to answer them.

Each of these steps should contribute to the ultimate aim of any data strategy, which is to create a single point of truth. Achieving that goal puts any organisation in the right place to embrace the opportunities offered by AI-driven data analytics, from improved customer service to increased productivity. To stay competitive in today’s fast-paced business environment, it’s a must.

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Matthew Beale is a Modern Data Architect at Ultima Business Solutions, an automation and transformation partner. You can contact him at [email protected] and visit Ultima at www.ultima.com

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