Big Data Analytics
There is a significant distinction between data and information. We assist you use your data to urge the precious and actionable business information.
The first step is to understand what kind of information is valuable for your business and what sort of questions you would possibly want to answer. We assist you with defining the KPIs and identifying the data sources. Then we make the data easily accessible, building a suitable data infrastructure if necessary.
Depending on your use cases and particular business needs we may propose you a data warehouse with Business Intelligence reports and dashboards. In some cases a data lake may be more appropriate. Great variety of data and data sources, very large volumes of non-structured or semi-structured data, different purposes of data processing going beyond the typical business analytics – these are just some of the reasons to consider building a data lake. We assist you with setting the suitable analytical tools to leverage loosely related data coming from various sources to answer more complex questions than standard business reports can deal with. More sophisticated predictive analytics solutions using Artificial Intelligence and Machine Learning are also in our offer.
There is also a growing area of applications where one must deal not only with massive volumes of data but also to process them as they come. The processing paradigm shifts from periodically processing previously collected data batches to stream-processing at the time the data arrive. The development in IoT domain naturally creates many new cases where the data must be analysed in real-time. But stream-processing and analytics is not limited to IoT domain. In many other areas of business and technology it can be beneficial or even strictly required to reduce the latency in data collection and processing. If you are running an event-based system or if low latency is essential for any other reasons we can advise you how to build the suitable stream-processing data platform and stream analytics.