Introduction

In today's world, the proliferation of data makes the task of searching for relevant data a challenge for data analysts and data scientists. With data available not only in large volumes and different formats but also distributed in different locations, having a single window to explore all of it is of critical importance for their work. Only when they know where the data lives and what it represents will it eliminate the problem of finding the data that suits their needs best. Leading data management platforms allow enterprises to leverage Big Data from all data sources, in real-time, to allow for more effective engagement with customers, and increased customer lifetime value. Data management platforms give enterprises and organizations a 360-degree view of their customers and the complete visibility needed to gain deep, critical insights into consumer behavior that give brands a competitive edge.

Data Management Best Practice

The best way to manage data, and eventually get the insights needed to make data-driven decisions is, to begin with, a business question and acquire the data that is needed to answer that question. When you combine big data with high-performance analytics, organizations and enterprises should achieve include:

  • Simplify access to traditional and emerging data
  • Scrub data to infuse quality into existing business processes
  • Shape data using flexible manipulation techniques

With a Data Management system platform, enterprises can manage tremendous of data from all sources in a central location and give the most accurate business and customer information. Data Management is the first step toward handling the large volume of data, both structured and unstructured, that floods businesses daily. It is only through data management best practices that organizations can harness the power of their data and gain the insights they need to make the data useful.

Data Management Services

Modern computing systems provide the speed, power, and flexibility needed to quickly access massive amounts and types of big data. Along with reliable access, companies also need methods for integrating the data, building data pipelines, ensuring data quality, providing data governance and storage, and preparing the data for analysis. This is a data management system that is quite effective and most often used.

Database Management System (DBMS)

The first system that can be used for data management is a database management system, especially a relational DBMS. The reason is, this system can organize data into rows and columns containing all records in the database. Apart from relational DBMS, there are many other options to consider.

Data Integration

The second is data integration, which is the process of receiving voluminous types of data. Starting from the collection of information to its processing, the data will be "transformed" so that it can be accessed easily.

Big Data Management

In Data Management, it's focused on storage and processing data easily and securely. It's handled in data lake and data warehouse.

Data Analytics

In this step data will processing and analyzed to gain insight in Big Data. It's using machine learning and Artificial Inteligent.

Conclusion

Businesses need to seize the full value of big data and operate in a data-driven way-making decisions based on the evidence presented by big data rather than gut instinct. The benefits of being data-driven are clear. Data-driven organizations perform better, are operationally more predictable, and are more profitable.