Download the eBook: Simplifying the big data dilemma

Organisations that wish to grow understand that harnessing the power of data analytics and AI is crucial to success. To stand out from the competition and keep pace with digital natives, traditional companies need to have a solid data strategy and the solution to match. Only then can they bring clarity into their data lifecycle to accelerate growth.

Easy right? Well... not always. For organisations not born in the cloud, transformation is often a complex journey, it requires planning, strategy, and expertise. 

Our resident data and analytics guru, Sam Poursoltan, is here to help us understand the importance of data and analytics, especially the challenges organisations face and what they can do about them. 

Please tell us a little bit about your expertise and experience. 

My name is Sam. I'm a Principal Consultant who has worked in the technology and data space for more than 15 years, helping clients with the cloud data modernisation journey. My focus for the last seven years has been helping businesses improve capabilities in data analytics and machine learning (ML) across different industries, including retail, financial services, manufacturing, and healthcare.

In a nutshell, what is data analytics, and why should we care? 

Data analytics is often confused with business intelligence. While providing the necessary tools for business intelligence, data analytics is the process of examining datasets to extract valuable insights by uncovering the existing patterns. It helps businesses to make informed decisions by understanding processes, customers, and products.

When you speak with organisations about their data strategy, what are the biggest challenges they face? 

One of the main challenges I see is that many organisations are not moving fast enough to become data-driven businesses. They cannot analyse the data that will add value to their business. Often, they start working with the available data but cannot drill down or determine the critical insights because they can't create quality data products from their scattered and disjointed sources. 

The other common challenge, which relates to the first one, is making uninformed decisions about their data analytics solutions in a market that has a vast number of tools with different capabilities. This clearly requires extensive expertise in data analysis and engineering technologies that you cannot find in many organisations internally. Last but not least is the lack of sturdy data security and governance framework allowing organisations total control over their ever-growing data assets.

What is the piece of advice you would give leaders starting their journey to transform their data platforms?

The first piece of advice I would give is to try to fully understand your organisation's data culture. Identify what it is that's stopping you from scaling your business (while securing your data assets), and do not hesitate to seek advice from experts who have been in your situation or helped others before making decisions about your data journey.  

Learn more about data and how your organisation can start to untangle your data.

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