Limited insights

Do business opportunities remain uncaptured because modern and cutting-edge technology cannot be deployed like AI (Artificial Intelligence) or predictive analysis?

Situation: Need for advanced analytics everywhere

Data analysis is one of the most valuable practices for gaining a clear understanding of your business performance in today’s competitive market. To stay ahead of the competition and gain these important insights, it is necessary that you can make optimal use of the available analytical technologies on the market.

Challenge: Finding the right data science use cases and getting enough clean data

A common challenge nowadays is that there are a lot of ideas about data science. Many use cases might pop up in your organisation. Selecting the right use case to start with does not only require AI skills, but mostly business knowledge and knowledge of your organisation. It requires good understanding of the value of the use case AND the complexity of implementing it. Both from a data readiness perspective, as well as from a model perspective.

The bulk of work in AI projects usually sits in getting enough data ready for advanced analytics, like ML and statistical models. This is referred to as data preprocessing.

Solution: Advanced analytics & test lab

Sparkle has a team of business data scientists with a unique skill set combination: combining technical AI/ML knowledge with sound business knowledge. This will facilitate the selection of the right use case.

Data preprocessing work can be reduced significantly with a modern data architecture.

A modern data architecture is often cloud native and includes a test lab for data science experiments. The test lab can use structured and unstructured data from a data lake or any other data source within the platform. There is often additional data used in the data lab that’s not yet available in the organization’s data platform. If the experiments are successful and are also expected to return value on a recurrent basis, then the provisioning of this additional data sets is industrialized in the data platform and the AI models are deployed and monitored in production.

Do contact us to discuss how we can help you overcome your data challenges.

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.