Data Management Services

What is Data Management?

Data Management constitutes the standards, policies and processes that are in place to manage data efficiently at scale, ensuring its accuracy, quality, scalability, compliance, and interoperability.

In today’s world, businesses can keep one step ahead of their competitors by making fact-based decisions, thanks to data available to them. As examples, data can be used to assess acquisition deals, product launches, or even measure the value an individual employee brings to the company.

According to estimates, the world would have gathered 79.4 trillion gigabytes of data by 2025, waiting for significant insights to be extracted from them to support business success.

A data lifecycle begins with:

• Data Creation: Evaluating and collecting the necessary data from the abundant sources available like web, IoT devices, surveys etc,.
• Data Storage: Evaluating the types of data collected and then storing it, as well as ensuring the data infrastructure’s security and scalability.
• Data Sharing and Usage: Whether shared internally or externally, ensuring the data is securely available to the right business users for processing, discovery, and analysis.
• Data Archival: defining and implementing archival strategies for data. When data is no longer useful for daily operations, they can be archived and restored when needed. This is a cost-effective way to manage data.
• Data Deletion: The data that is not needed anymore is purged and destroyed at this stage of the lifecycle.

esynergy helps manage the entire data lifecycle from its creation to deletion. We help turn raw data into useful business insights to help our clients achieve maximal impact from the data they have access to.

Today’s organisations need a data management solution that provides an efficient way to manage data. Data management systems are built on data management platforms and can include databases, data lakes, big data management systems, data analytics, and more.

Data Mesh

A set of principles and processes in place to manage data at scale to ensure its quality and inter-operability.

Data Analytics

The endpoint for high-quality data to be analysed and used effectively using Artificial Intelligence and Machine Learning algorithms.

Data Governance

Data governance policies that are in place to outline how organisations manage the accessibility, integrity, compliance and security of the data.

Different requirements and scenarios need different tools and ways of working, and at esynergy we aim to provide the right data management solution for our clients to enable them to be data driven.

But data and the efficient and effective use of it, has its own set of challenges that must be overcome for it to drive the desired value.

Difficulty managing IT resources

The growing volumes of data, if not managed properly, make it increasingly difficult for businesses to utilise it effectively. Scalability in terms of storing and processing large volumes of incoming data, improving performance levels through fine tuning the system’s resources all require specialised skills.

Collecting and identifying the data itself doesn’t provide any value—the organisation needs to process it. It is essential for businesses to have systems that allow them to convert data quickly and efficiently into the information they need for analysis.

In the past, esynergy has helped deal with issues related to large amounts of data that made their systems and analytics slow moving. We developed an Azure-based scalable data management solution for them, through which they gained accelerated insights into their data, unlocking its true potential.

Compliance issues

Data storage and usage regulations are complex. There are regulations regarding how one can store medical data, card and payment details, and regional compliance laws like GDPR that should be adhered to. Moreover, these laws are constantly changing. It is important for organisations to be able to easily review their data and identify anything that falls under new or modified requirements.

Without a good data management process, keeping track of these constantly changing regulations becomes increasingly challenging.

Data Quality and Accessibility

Data collected by organisations can come from a wide variety of sources, like sensors, smart devices, social media, surveys–all in different shapes and sizes–requiring to be normalised and processed. It is important for the teams owning the data to ensure it is in the right format, usable, high-quality and accessible–without which effective and quick data-driven decisions cannot be made.

Successful data management solutions from esynergy have enabled our clients to ensure that their data is high-quality, easily accessible that their cross-functional teams use for faster insights.