Types of Data Management Tools: A Comprehensive Guide

Data management tools have features such as archiving, backup, disaster recovery, archiving, search, analysis and more. This article explores each type of tool in detail.

Types of Data Management Tools: A Comprehensive Guide

Data is a valuable asset for any company, and managing it effectively is essential to gaining a competitive advantage and improving customer experience. Data Management (DM) is the process of collecting, storing, and using data in an efficient, secure, and cost-effective manner. There are various types of data management tools available to help companies manage their data, such as master data management tools, cloud data management tools, data integration and ETL tools, data transformation tools, reference data management tools, and data analysis and visualization tools. In this article, we will explore each of these types of tools in detail.Master Data Management Tools are designed to help organizations manage their master data.

This type of tool helps to create, locate, or access verified data when needed. Some of the functions of Master Data Management (MDM) include data security, data integration, data quality, and business process management. Notable examples of MDM tools include Oracle Data Management Suite and IBM Infosphere Master Data Management Server.Cloud Data Management Tools are designed to help organizations store and manage their data in the cloud. Amazon Web Services (AWS) provides a range of tools to help achieve a successful cloud data management stack.

These include Amazon S3 for temporary and intermediate storage, Amazon Glacier for backup and long-term storage, AWS Glue for creating data catalogs to categorize, search, and query an organization's data, and Amazon Athena for SQL-based analytics to create dashboards and data visualizations. Microsoft Power BI is another popular cloud-based tool that enables teams to make quick, data-driven decisions.Data Integration and ETL Tools are designed to help organizations move, store, and analyze their data from multiple sources. IBM InfoSphere Information Server is a scalable on-premises and cloud ETL platform that enables companies to explore, analyze, and understand all their data. It can be deployed on Windows or Linux systems in the cloud or on local servers.

It also provides intelligent real-time data blending, data collaboration and analytics, plus actionable worksheets and dashboards.Data Transformation Tools are designed to help organizations convert raw data into a format that is easy to understand and analyze. Looker is a business intelligence and big data analysis tool with excellent visualization and reporting capabilities. It allows users to easily explore, analyze, and share reports in a wide range of formats to suit different requirements. Tableau is another popular interactive visualization tool that allows companies to see and understand their data quickly and easily.Reference Data Management Tools are designed to help organizations manage their reference data.

Panoply is a cloud-native tool that allows companies to synchronize, combine, and store their data from more than 80 different sources. It also provides the ability to visualize data with a wide range of analytical and business intelligence tools.Data Analysis and Visualization Tools are designed to help organizations analyze their data. Ataccama ONE is an automated database management software that can be run in the cloud, on-premises or in a hybrid configuration. It includes features such as DAGs that help distribute scheduler tasks to other workers without defining any parent-child relationships in the middle of the data flow stack.

It also provides seamless connectivity and integration with different types of data sources with the help of ready-to-use connectors.In conclusion, there are many types of data management tools available that can help organizations manage their data effectively. Each type of tool has its own set of features that can be used to meet specific needs. By leveraging these tools correctly, organizations can gain insights from their data quickly and easily.