EMPENOFORE has built a substructure for its customer organizations to remodel their traditional data applications- Operational Datastores (ODSs), Data Warehouses, other data platforms, also practices within data warehousing and enterprise data management. The substructure covers reshaping across the extents of Data Sources types, data delivery, data design and pattern, data landscape, and governance.
One of the most common problems faced by organizations is Information overload. To endure the problem they turn to the automation of intuitive reports, scorecards, and visualizations. Modern business intelligence solution with smart dashboards and visualizations is the upshot.
To get a hold in data science and AI in their solutions, businesses are joining Data and Analytics practitioners. Therefore, Empenofore consists of a prepared team of Data Scientists. Their role is to design innovative solutions that incorporate a new set of tools and technologies across ML and NLP.
We top-up data foundation to build a range of analytics solutions. Develop economic storage for loading data in a near-native format.
It provides an interface for programming entire clusters with implicit data parallelism and fault tolerance.
It provides a software framework for distributed storage and processing of big data using the MapReduce programming model.
Enterprises can create and process predictive analytics models with Cloudera. Includes the core Hadoop Technology.
Integration with the Azure Data Lake Storage Gen2. Provides cloud-based business analytics. An easy-ramp into Big Data.