Data Warehouse & Data Lakes

Every organization builds Data Analytical Platforms for analyzing business operations
to get insights and foresights.
We work with both Analytical Platforms like
  • Traditional Data Warehouse
  • Data Lakes

Our Activities

Data Analytical Platform

Data is being a blood line for multiple organization to run their business and strategies the management decisions. We have two different types of analytical platforms in the organization as of today, one the traditional Data warehousing technologies and newer Data Lake technologies.

Traditional Data Warehouse

As a company, we are well versed with both Bill Inmon way of implementing the Enterprise Data warehousing (CIF Approach) and Ralph Kimball way implementing the Data Warehouse (Data Mart Approach). Corporate Information Factory (CIF) approach is the top down approach where all the raw materials are readily available to mold any model / generate any report business needs. Data Mart approach follows the bottom up approach, we can call it as objective based solution as the problem is predefined and the end result is visualized. Based on the resources available in the organization, Data team picks the suitable model to implement.

Data Lakes

As the cloud adoption, storage and computation advancements, the newer platform to consolidate and integrate data came into existence. Data Lake’s purpose of existence is as same as Data warehouse, but the principles and processes are a bit different. End users of Data Lakes are not only business users (as in DW), here end users are Data Scientists and other analytical users. Here we tend to store data in raw data to increase the flexibility of usage. The accessibility of this data is very high. We store all kinds of data (structured, semi structured and un-structured) in the Data Lake. In the traditional data warehouse we have to convert all the events, information into a structured form so that business professionals can understand. As the ML and AI is in the mainstream in different domains, the data lake utilization is very high as the need keeps changing very rapidly until we optimize the model to the acceptable business clause. Data Lakes are typically created with a cloud infrastructure or in an on premises Big Data Platform. We worked in AWS Data Lake, Azure Data Lake and Big Data technologies to implement Data Lakes for our customers.

Projects are in Data Warehouse

Technologies Uesd in Data Warehouse

SQL Server

Azure cloud

Data Factory
Power BI

Azure Storage


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