Big Data Analytics


Big Data Analytics

The success of your data science project is only as good as the data it uses. But, as companies collect siloed, inconsistently formatted data from different sources and in huge amounts – AKA big data – flaws creep into the final algorithm and simply sabotage all your ML efforts. Big data engineers are the ones responsible for all big data analytics groundwork. They handle facts that data scientists use later to turn into AI models, find and manage data sources, and establish your organization’s data management.

Structured data is useful data, so managing huge volumes of data starts with designing and creating a Data Warehouse or modernizing your legacy DWH to fit current technological standards and scale, increase performance, and reduce costs. To help your people easily access the data they need, we create data lakes that will nourish your data-driven efforts. And to finally process all this data, we build applications using technologies like Hadoop or Spark to process data streams in real time. Data engineers at UMCG will find, organize, and store big data for your project, either as a part of your own IT department or as an extended team.

Our Data Engineering and Big Data Services

Reviewing your current data architecture to analyze data sources and define data lakes or DWHs

Cleaning, processing, and transforming data into usable formats for model development.

Building data pipelines that gather, process, store, and help access data.

Consult on selecting the best fitting open source or proprietary big data analytics tools and products for your project.

Helping choose among big data platforms for managing your data infrastructures, such as Cloudera, AWS (Amazon Web Services). Microsoft Azure, Google BigQuery, Teradata, SAP, IBM, Oracle, and more…