At Cerebra, We help you with building a trustable data foundation by identifying the right data, developing a Data Governance Framework, Data cleansing and organizing it in to a data model.
To make effective use of the available data, we need to build the right foundation which involves identifying the right data to be processed of the available quintillions of bytes of data.
At Cerebra, our expert data analysts will interact with the business users to understand the business strategies and requirements and help in finalizing the data set which will enhance the business decisions and potential market risks.
Organizations need more than just Data management system. They need a Data Governance Framework that sets rules and compliance to address data inconsistencies across the different departments and data ownership issues to meet the growing needs of Big Data and the various advantages that it offers.
At Cerebra, we help organizations in creating guidelines and rules, to ensure that these are being followed and then deal with ambiguities, noncompliance and other issues. A data governance framework is built, which allows them to make informed decisions about how to manage data and eventually realize value from it, minimize cost and complexity, manage risk and ensure that the organization can fulfill the ever-growing demand for compliance with regulatory, legal and state requirements.
Data cleansing is the process of altering the data in the data management system to make it more accurate and error-free. It involves deleting old, incomplete or duplicate records which are not relevant and also parse the data to get rid of typographical errors or to validate the data is compliant to the Data Governance Framework rules.
At Cerebra, we use various data cleansing tools to effectively make the data error-free and compliant.
Data modeling is the concept of organizing the data to fit the needs of Business Processes. The traditional data modeling involves relational database technologies where the logical relationships of the data are designed to fit the business requirements. These logical designs are then transformed to physical designs to be implemented on the storage devices that have the actual data.
With the evolution of Big Data and considering the huge volumes of data involved, the traditional data modeling techniques are not relevant anymore. NoSQL systems are “schema-on-read” that is data can be dumped into it without a schema but when retrieving a model is imposed.
At Cerebra, our Big Data Analysts will use the big data tools like Hadoop and terdata to create a data model which are defined and used dynamically in the fly.