ExistBI is able to address the continuous growing demand for Big Data Analytics services. This concept of data analysis and deriving useful information from large volumes of data that are rapidly being generated in modern business – from conventional database systems to unstructured data gathered from location, sensor sources and social networks.

It is ‘Big Data’ best practice is to create a Data Lake solution or Big Data Data Warehouse vs. the traditional Enterprise Data Warehouse – Industry experts consider Data Lakes as the new Modern Data Warehouse. The concept of the Data Lake is to store structurally and spatially heterogeneous data sources with complex storage modes reliably. These data sources would then be accessible at any time to help support your optimal business decisions.

As a leading Big Data Analytics service provider, our Big Data and Hadoop consultants are required for successful preparation, design, development and implementation of Big Data Processing and Analytics systems based on standard platforms. We offer two specific service packages, described in more detail below:

Big Data Consulting & Assessment

Would you like to start your first Big Data initiative, but you are not sure what to do and how to create value for your Company? You don’t have a clear picture of investment and resources you need to secure and what benefits you can expect? You would like to protect your existing investment in IT infrastructure? Our Big Data Assessment is carried out by an experienced Big Data professional. Based on the information gathered from the stakeholders through a series of workshops, a strategy and plan of action is created.

Big Data Consulting & Implementation

We have teams of Big Data consulting specialists and experienced Hadoop developers ready to work on your Big Data Warehouse and Big Data Analytics projects.

Our teams experience includes, but not limited to:

  • Apache Pig to execute Hadoop jobs in MapReduce, Apache Tez, or Apache Spark
  • Data streaming and collection with Apache Nutch and Flume
  • Data transformation and integration with Hive, Pentaho Kettle, Informatica and Microsoft SSIS
  • Databases including: HBase, HDFS, MongoDB, Cloudera Impala, Cassandra, Neo4J, Couch DB just to name a few
  • Semantic analysis using Knime, IBM SPSS, Microsoft
  • Visualizations using Tableau, Microsoft Power BI, Pentaho and various other front end platforms.

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