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The data analytics domain has been disrupted by the surge of pure-play digital business models at web-scale. Social media, streaming video and e-commerce business models have researchers, companies and open-source enthousiasts to developing new ways of tackling classic data analytics challenges that were too complex or too expensive to deliver.
Our applied data analytics portfolio is an agile, modular approach to applying the insights from the global innovators, to the early adopters and early majority.
By focusing on innovative methods and taking them mainstream, we are able to solve a number of classic challenges in data analytics:
Investing in a cloud-first strategy for business intelligence offers considerable value opportunities for new and experienced data analytics teams. We help realising the potential in a bespoke and progressive way.
Support your managerial processes with timely and consistent data.
We build user-friendly information portals that scale from tens to thousands of users without performance impact.
Stand-alone or embedded in applications such as Salesforce.
Improve the data literacy of your workforce by granting controlled access to company data assets.
Set up governance processes to ensure maximum service levels while remaining within safe compliance boundaries such as GDPR and PCI/DSS
Beat time-critical planning & budgeting processes by automating manual data collection and correction.
Set up planning, budgeting & forecasting workflows to consolidate human intelligence on the market's next moves.
Augment the capabilities of your business teams with automated decision rules. Optimize the outcome of your operational processes with best-case scenarios.
Machine learning, data science and artificial intelligence come with a new wave of techniques, terminology and methods of interpretation.
Our Analytics Translators help at capitalizing on new insights by translating numerical insights into business language.
Build automated decision rules based on large historical data sets.
Our machine learning engineers build datasets and infer insights based on cloud technology.
Operationalize automated decision models. Our cloud engineers deliver API’s, datasets and integrations based on your current or future enterprise architecture.
The quality of automated decision models decays over time. Our practices in model lifecycle management helps to build trust in blackbox ML models.
Act on data as soon as it is registered. Our reference architecture on streaming data platforms assists at building future-proof data platforms to process data in streaming- and batch mode.
We help enterprise architecture teams at understanding and designing event-driven data backbones.
Analyze data in-flight and apply complex logic to events.
Replicate your operational systems to your warehouse as soon as change happens.
We built frameworks on standard AWS services to synchronize transactional and analytical systems.
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Get to know the cloud-first data warehouse on our joint free breakfast event on March 3 2020 in Brussels (Belgium).