Data Management

Data is the Soil for an organization. By managing it very effectively
we can add value to business and monetize it on
various opportunities.
  • Structured / Repetitive Data
  • Semi Structured / Non Repetitive Data
  • Un Structured Data

We provide our servies in the following activities

In the current environment we live in, we tend to capture all the events in a business. As we are capturing every heart beat in few businesses, the velocity of the data defines the usage of the technology as well. The faster we get the data, the better the infrastructure should be. Typical transactions in million transactions a day is taken care by traditional RDBMS, anything we have options to choose from NoSQL to Big Data technologies as our Data Storage option.
We have different technologies in play to capture the different kinds of data

1)Traditional Tabular Structure & Columnar Structure way of storing Data (RDBMS)
2)NoSQL Databases to capture the Semi Structured Data (more flexible and scalable)
3)Big Data & Object Storage to store Un Structured Data

Our Activities

Data Re-engineering

Data reengineering extends the life of existing systems by standardizing data definitions and facilitating source code simplification. It can also provide an accurate data model for use as a starting point in data modeling and database technology migration and as a preparation step for reverse engineering.

Data Processing

Data processing occurs when data is collected and translated into usable information. Usually performed by a data scientist or team of data scientists, it is important for data processing to be done correctly as not to negatively affect the end product, or data output.

Data Architecture

Data Architecture “includes specifications used to describe existing state, define data requirements, guide data integration, and control data assets as put forth in a data strategy.” Data Architecture bridges business strategy and technical execution, and according to our 2017 Trends in Data Architecture Report

Data Analysis

Data analysis is defined as a process of cleaning, transforming, and modeling data to discover useful information for business decision-making. The purpose of Data Analysis is to extract useful information from data and taking the decision based upon the data analysis.

Data Migration

Data migration is the process of moving data from one location to another, one format to another, or one application to another. Generally, this is the result of introducing a new system or location for the data. The business driver is usually an application migration or consolidation in which legacy systems are replaced or augmented by new applications that will share the same dataset. These days, data migrations are often started as firms move from on-premises infrastructure and applications to cloud-based storage and applications to optimize or transform their company.

Projects are in Data Managment

Technologies used in data managment