fbpx
Features Hub Interview

Harnessing legacy systems to drive data insights

Wed 6 Mar 2019 | Sam Sibley

Exploring the misconceptions surrounding data-driven transformation, with Sam Sibley, partner and alliance manager for UK & Ireland at Exasol

A core component of digital transformation is data transformation: transforming your organisation to be data-driven, to drive business value. The benefits of being data first are now clearly established: predictive maintenance, supply chain optimisation, the generation of new business models and the improvement of the enterprise’s customer-facing activities.

As with any technological transformation, success depends on both the technical (e.g. data sources/orchestration) and business foundations (e.g. cultural change). It’s a common misconception, however, that refining the technical foundations requires replacing existing legacy systems. Enterprises are all too unaware of what can be achieved with the technology they have.

Sam Sibley, partner & alliance manager for UK & Ireland at Exasol is on a mission to inform enterprises about the business value that can be achieved from their existing IT stack. As he explains, to become data-driven, the edge comes not necessarily from upgrading, but leveraging sophisticated analytics software to complement existing tech; optimising what you already have. Does this mean enterprises should hold onto all of their legacy tech?

“Of course, depending on the use case or business functions, there’ll be instances where you’ll want to gradually phase out some of the legacy systems as you develop your strategy,” Sam says.

“The true challenge of legacy systems lies in the complexity of maintaining them and in their lack of flexibility. So, in those areas where you need to be fast, agile and flexible, you will need to modernise but there’ll be other areas where your legacy system will still deliver what you need it to.

Top-shelf transformation

Utilising best-in-class analytics software does not only allow firms to leverage existing systems. It also translates to more efficient data access and analysis, competencies that themselves produce faster actionable insights which allow stakeholders to make more informed decisions and improves business agility.

“It is important to remember that data is a valuable asset so long as you can access and make use of it,” Sam says. “People often start with looking at what they want their business intelligence (BI) tool to help them achieve but they forget that BI insights can only be as good as the data fed into the BI tool. So, the initial focus should be on what data you have available and how/if you can access it.”

I ask Sam what the process of data-driven transformation looks like from a firm’s perspective. The first step he says involves assessing present and potential data supply. Not every solution scales the same, so ‘you want to make sure you invest in a technology that can grow with your business’.

It is imperative firms do not become data-impotent for any period of time. Shifting technologies is not only cumbersome and costly, but any time sat on an unexploited data stockpile is precious time for competitors steal an edge.

The next step is to establish what systems you already have and how they work. A truism (that nonetheless bears repeating) is that no two firm’s needs are the same.

Some may need to replace all systems, some simply to improve existing systems – until that that preliminary analysis is made there is no point diving into a service.

“Not all data analytics technologies can work seamlessly with all legacy technology, so you’ll want to make sure you select a vendor that can adapt to your specific needs.”

“In those areas where you need to be fast, agile and flexible, you will need to modernise but there’ll be other areas where your legacy system will still deliver what you need it to”

A final component, Sam says, is establishing your broader infrastructure strategy: whether you’re migrating to the cloud, remaining on-premises or opting for hybrid deployment.

“Again, not all technologies work in all scenarios, so you want to carefully think about where you are and where you want to go to make sure your vendor of choice can go with you.”

Too big to fail, but not too big to save

Badoo is one firm that has seen immense value from opting for a service that worked within their existing ecosystem. Badoo, the largest dating website in the world, soon saw its colossal data volumes outgrow its existing infrastructure. They needed a platform that could manage its mammoth data volumes and deliver results in real-time, without throwing out legacy systems.

“As a company that strives to accelerate time to love in the digital age, this was a big challenge that needed solving, fast,” Sam says.

As Sam explains, with Exasol, Badoo receives real-time feedback when setting up A/B tests, giving it room to manoeuvre. When the tests are defined, the database tells you if there is an overlap and how big it is – which can scale up to the millions. Since this initial success, their partnership has extended further.

“The R&D teams develop features together to make the product even better, and thanks to Exasol’s self-tuning technology, upgrades can be done without delays, so the quality assurance cycle has been accelerated.”

‘Start small but think big’

I ask Sam to offer his final takeaway for businesses in the throes of or planning a digital transformation project. He says the key is to start small, think big, and begin with data.

“Ask yourself these questions: ‘What data do I have today?’ ‘what data could we have tomorrow?’ and, ‘how do we make that accessible to the business?’ Develop your data strategy carefully and find a platform that can help you harness it to address your business objectives. The rest of the project will follow.”

Join me at Big Data World.

Sam is presenting at Big Data World 2019. BDW and its co-located events attract over 20,000 IT business leaders, decision makers and influencers.

Experts featured:

Sam Sibley

Partner and Alliance Manager, UK & Ireland
Exasol

Companies featured:

Tags:

Big Data Cloud data analytics
Send us a correction Send us a news tip




Do NOT follow this link or you will be banned from the site!