Big Data solutions

The AM-BITS team of certified Big Data engineers ensure the end-to-end development, building and implementation cycle of solutions based on Apache Hadoop.

Collected business data must provide enterprises with additional competitive advantages via better interaction with customers, faster response times to events, improved forecasting, etc. However, traditional data storage systems just fail to process large-scale volumes of repository data, and timely respond to online data streams.


Our innovative Big Data solutions allow to solve any business tasks of managing large enterprise data in the most effective and cost-efficient way, thus providing a number of advantageous features:

  • Optimal storage
  • On-time processing
  • Information analysis
  • Forecasting

Our cases in the category of Big Data solution

A cost-effective solution providing scalable storage capacity for enterprise Big Data sets.


To transfer rarely used data and part of ETL processes to Hadoop. Also, to utilize data virtualization to build a data mart for BI.

An increase in ROI of 200% and 500% for levels 1 and 2, respectively. Cost reduction of up to 75% on data organization and provision for further analytics.

Creation of a multifunctional center for aggregation, processing and presentation of data along with secured real-time exchange of enterprise data.


The structure of functional components:

  • Data Broker (Kafka) – ensures real-time data exchange.
  • Big Data Platform (Hortonworks / Cloudera Hadoop Data Platform, Hadoop Data Float) – stores all data coming through a data broker.
  • Logical Datawarehouse (Tibco Data Virtualization) – a logical data warehouse, a tool for business users to access and manage data. Also, it enables fast data access for online monitoring of the end-to-end technical process (from data collection to data usage), and provides data for technical monitoring.
  • Data Governance – data management, includes data quality and security.

Scalable architecture built on Apache Kafka for real-time data exchange, 24/7. The number of processed events is about 2-3 million per day, and up to 200 events per second. Optimization of data governance, with regard to data quality and security.

Request full cases:

Big Data Warehouse ExtensionEnterprise Data Hub: Development and IntegrationMeasurement of Employee KPIs