Data Engineering

Core Areas

Data Lake Implementation

We believe all organizations should generate business value from their data. A data lake is a repository that facilitates this by storing structured and
unstructured data in any format. Big data processing, machine learning algorithms and real-time data analytics are used on a data lake to inform decisions.

1
Collect
2
Ingest
3
Blend
4
Transform
5
Publish
5
Distribute

Business Intelligence (BI) and Analytics:

Our data engineering team can work with any modern data stack, including Apache Hadoop, Apache Spark, Apache Flume,
Elasticsearch, Apache Solr, Horton-Works Open and Connected Data Platforms and NoSQL Platforms like Apahe Cassandra, Apache Hbase.

Our team strives to find the “nugget” of data that is actionable through analytics engines and present it in a timely manner to the decision-makers.

We make data work for you.

In order to support and validate data-driven decisions, our team:

Designs and implements Data warehouse

Gathers test data to train analytics engines and implements them

Structures appropriate ETL processes

Designs and develops Dashboards

Data Engineering Tools

An Informatica Partner with expertise in:

Data Profiling

Master Data Management

Address Validation

Data Quality Management

Data Transformation

Information Life Cycle Management

Dynamic Data Masking

Let us make data work for you.