Data Management

The data management process includes a combination of different functions that collectively ensure your corporate data is accurate, available, and accessible.

Today, data is a corporate asset that is capitalized to make informed business decisions, optimizing business operations with an overall goal of increasing revenue and profits. As companies capture large volumes of data, they are subjected to increased compliance and regulatory standard and privacy laws, such as GDPR (General Data Protection Regulation GDPR), etc. This makes data management inevitable, the lack of which makes it near impossible to navigate big data systems, leadings to data silos, inconsistent and poor data quality, and limits the ability to implement BI and Analytics applications and in the worst case leads to faulty predictions.

Challenges due to lack of data management

  • Disparate Data sources
  • Sluggish Database performance
  • Unstructured Data
  • Data Security
  • Data Governance
  • Unable to implement a BI strategy

Our Data Management Strategy

Traditionally data strategy has always revolved around storage and continues to remain for most companies. While this is an important aspect of data management, it does not have much room for data accessibility and shareability. Data management today involves identifying, storing, processing, analytics, and governance. As shown in the figure above.

How we help

As AWS and Microsoft partners, we provide both consultation and implementation services for your data management strategy, either from scratch or help optimize your existing data management practices.

Our data management strategy aligns with modern big-data practices that help you get the maximum benefit from your data assets by providing data, which is accurate, clean, highly available, and securely accessible with data governance baked in.

Data lakes and Warehousing

Move and combine structured or unstructured data residing in multiple sources, and provide a unified, consistent data view. Run SQL and complex, analytic queries against structured and unstructured data on them, without the need for unnecessary data movement.
We can help you set up data warehouses and data lakes on leading cloud platforms such as AWS & Azure.

Data Migration to Cloud

Migrate SQL Server, Oracle, DB2, PostgreSQL and MySQL database, and at scale from multiple sources to cloud. Our cloud team uses a mixture of software tools and consultancy best practices to provide you with a plan that best suits your requirements.
Avail our AWS and Azure Data Migration Services.

Data Processing

Scattered data is of very little value as is raw data. Integrate data from multiple sources, process it for use in your desired format, and finally load it into a Datawarehouse, while maintaining the security and integrity of your data. This process also known as ETL (stands for extract Transform and Load) is crucial for BI implementation.
Our team can help you implement ETL process for data preparation or use it for advanced analytics with tools such as, Azure Data Factory, AWS Glue, Hevo data, Talend, Alteryx, AWS Data Pipeline to name a few.

Data Analytics​

Whether you are looking for Real-time or Operational Analytics, we got you covered. Perform analytics operations such as search, explore, filter, aggregate, to enable real-time application monitoring, log analytics, and clickstream analytics. Collect, process, and analyze streaming data, and load data streams directly into your data lakes, data stores, and analytics services. Get self-service analytics, interactive dashboards, BI portals in Tableau, Spotfire, or Power BI.
We can help you with actionable insights into your data with modern visualization.

Why Us?

Gain competitive advantage, put your data assets to work. Let’s Collaborate!

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