Legacy IT limitations

Are old IT systems difficult to renewed? Does data remains locked due to limitations like accessibility, weak integration options and performance?

Situation: A typical organisation has a complex data landscape with many limitations

Over the years, as your company has grown, the IT department has become responsible for several database systems that support business-critical functions, such as Finance, Customer Relationship Management (CRM), stock management, distribution and human resources.

Your company now runs many different database servers with different version numbers and from different vendors. These legacy systems cannot be easily centralised or replaced, because the cost-benefit is too high, or because the business would be impacted too much.

Challenge: Data that is locked in IT systems is preventing novel insights for business

The existing legacy IT environment is crucial for your business and works well, but they have limitations and are missing modern data features. The data that resides in the legacy system is not easily retrievable or there is a fear that changes might result in rework down the road.

Organisations are missing insights from legacy systems because the data is locked and not easily accessible. A lot of budget and resources is spent just to keep the lights on.

Once a decision is made to upgrade or migrate an IT system, a significant amount of budget and resource is spent to redo the data integrations that allow insights of data that resides across multiple systems.

Solution: Modern data platform can unlock novel data insights

Thanks to modern technologies like CDC, it is possible to unleash the data from legacy databases without impacting the applications. What we often see, is that there are still databases (and applications) on mainframes that cannot be easily migrated. There are years of development and business rules hidden in the code, developed by people that have left the organization (or retired). This results in high cost (MIPS) and a lack of flexibility (nobody dares to change the system).

With change data capture, the legacy database can just keep running, but the data can also be immediately transferred to a modern data platform. Other applications that need this data retrieve it from the new platform (reducing MIPS on the mainframe). Furthermore, the data can be further transformed and enriched on this platform without impacting the legacy database and application.

Setting up a modern data platform according to the Sparkle’s reference architecture can help gaining novel insights, without a dependency on the underlying old/legacy source systems. Thus allowing possible migrations of source systems to happen without significant impact on the data platform or reports. This will allow your organisation to invest in innovation that brings immediate value, rather than spending vast amounts of money to keep the lights on.

With data platform modernisation you can streamline your data across IT systems and remove barriers, so your business can achieve its strategic objectives and goals. A modern data platform is capable of fulfilling the current and future (+/-5 years) data needs. It is often cloud native, integrates data from multiple systems, and is cost efficient to setup and maintain.

At VAR we are modernizing our application landscape. We wanted to take the usage of data to the next level. With Sparkle, we introduced speed and efficiency in the setup of a modern data platform. The data platform is fed in real time and has not only delivered new insights, but has also become a crucial part of our enterprise architecture.

The organization encountered the need to develop its experience in Business Intelligence. We hired Sparkle and they did not only deliver the right experts, but also helped us finetune our strategic objectives and setup support structures. The pragmatism and maturity of the Sparkle consultants fits really nice within our team.

The operators of the traffic centre get too many traffic alerts and needed a way to filter out only the real incidents. Sparkle (previously Lantana) analysed with different AI methods if a prediction of real alerts was possible. It gave us very goods insights in the data and we decided to improve the granularity, the quality and the quantity of the data.

Sparkle is helping us setting up data governance and enterprise data architecture within our organization. We needed a partner that was capable of tackling several data related challenges from a holistic perspective, with a high level of expertise and yet with a pragmatic approach. We are happy with the highly skilled and qualified services Sparkle offers.

With the help of Sparkle it became more clear what aspects of data we had to focus on and how to build it. Sparkle also helped our health tech startup with finding already existing API’s and methodologies which saved us a lot of time.