Data Management is as successful as the tools used to store, analyze, process, and discover value in an organization’s data. In essence, these tools are heterogeneous multi-platform management systems that harmonize data.
The most widely used data management tools belong to the industry’s biggest software groups whose experience guarantees a high degree of performance, security, efficiency, effectiveness, elimination of data redundancy, and privacy that is necessary for companies that are leaving the entire organization’s information in the care of external vendors.
1. MS Excel
- Spreadsheet software that tracks data in columns and rows Spreadsheet software that tracks data in columns and rows
- You can perform calculations on data and show graphs You can perform calculations on data and show graphs
2. MS Access
- A type of Relational Database A type of Relational Database
- Data is stored in tables that can be related to each other via Data is stored in tables that can be related to each other via common IDs common IDs
- Data can be manipulated via Queries Data can be manipulated via Queries
- Data can be entered via Forms and retrieved via Reports Data can be entered via Forms and retrieved via Reports
3. Oracle Data Management Suite
Comprehensive platform that delivers a suite of solutions that enable users to build, deploy, and manage data-driven projects by delivering consolidated, consistent, and authoritative master data across an enterprise and distributes this information to all operational and analytical applications. It enables data governance and quality, policy compliance, repeatable business processes, cross-functional collaboration, and change awareness throughout the enterprise.
4. SAP Data Management
Integrated technology platform that uses a single point to access all data, whether transactional, analytical, structured, or unstructured, across on-premise and cloud-based solutions. It provides access to metadata management tools to enable an intelligent data management process by taking advantage of the cloud benefits, which include low cost of ownership, elasticity, serverless principles, high availability, resilience, and autonomous behavior.
5. IBM Infosphere Master Data Management Server
A comprehensive tool that helps manage enterprise data to present it into a single trusted view and deliver analytic capabilities. It includes a security system, transaction control, multi-domain support, event management and data quality analysis. It manages all aspects of critical enterprise data, regardless of system or model, and delivers actionable insights, instant business value alignment, and compliance with data governance, rules and policies across an enterprise. IBM Infosphere orchestrates data throughout the complete information lifecycle.
6. Microsoft Master Data Services
Platform that includes a suite of services that enables users to manage a master set of an organization’s data. Data can be organized in models, it can be updated by creating rules, and it can include access controls to authorize who updates the data. It enables users to develop MDM solutions that are built on top of an SQL Server database technology for back-end processing. It provides service-oriented architecture endpoints using Windows Communication Foundation (WCF) and it implements a hub architecture using MDS to create centralized and synchronized data sources to reduce data redundancies across systems.
- Microsoft Azure Data Factory: It is a hybrid data integration service that simplifies ETL at scale and is specifically designed for all data integration needs and skill levels. With its rich visual environment, users can easily construct ETL and ETL processes in a code-free fashion by integrating data sources from more than 80 natively-built and maintenance-free connectors.
- Microsoft SQL Server SSIS: Microsoft SQL Server Integration Services (SSIS) is a platform for building enterprise-level data integration and data transformations solutions. It solves complex business problems by copying or downloading files, loading data warehouses, cleaning and mining data, and managing SQL Server objects and data. Additionally, it extracts and transforms data from a wide variety of sources such as XML data files, flat files, and relational data sources, and then loads the data into one or more destinations. The platform includes a rich set of built-in tasks and transformations, graphical tools for building packages, and the Integration Services Catalog database to store, run, and manage packages. Last but not least, it allows users to leverage the graphical Integration Services tools to create solutions without writing a single line of code.
- Microsoft Power BI: Business analytics service that delivers insights to enable fast, informed decisions. It helps transform data into compelling visuals that can be shared on any device to visually explore and analyze data, on-premises and in the cloud, all in one view. Additionally, it enables collaboration through customized dashboards and interactive reports, and it scales easily with built-in governance and security.
7. Dell Boomi
Enterprise-grade platform that is unified and versatile, leveraging all the advantages of the cloud. The platform is designed to provide ease of use and high productivity by:
- Connecting all applications and data sources across a hybrid IT landscape.
- Synchronizing and enriching data through a centralized data hub.
- Achieving interoperability between internal systems and external partners.
- Exposing underlying data as APIs to deliver scalable and secure, real-time interactions.
- Transforming manual processes into automated processes with flexible business logic and workflow capabilities.
Single, open platform for data integration, data management, enterprise application integration, data quality, cloud storage, and Big Data across cloud and on-premise environments. It helps transform data into business insights to help companies make real-time decisions and become data-driven.
Interactive data visualization solution that helps users see and understand data. It helps simplify raw data into an easily understandable format for smart data analysis. Visualizations are created in the form of dashboards and worksheets through its key features that include data blending, real-time analysis, and data collaboration.
10. Amazon Web Services - Data Lakes and Analytics
Integrated suite of services that provide the necessary solutions to build and manage a data lake for analytics. AWS-powered data lakes are capable of handling the scale, agility, and flexibility required to combine different types of data and analytics approaches to gain deeper insights. AWS provides a comprehensive set of services to move, store, and analyze data.
11. Google Cloud - Big Data analytics
Solution platform that offers a broad set of tools for cloud-based data management, as well as a workflow manager to tie components together such as BigQuery for tabular data storage, Cloud BigTable for NoSQL database-style storage, Cloud Pub and Cloud Data Transfer for data intake, ML Engine for advanced analysis via machine learning and artificial intelligence, Data Studio for GUI-based analysis and dashboard construction, Cloud Datalab for code-based data science, and connections to BI tools such as Tableau, Looker, Chartio, Domo, and more.
There are also a number of emerging data management tools from relatively small vendors that are worth mentioning:
12. Looker BI
Business intelligence software and Big Data analytics platform that helps users explore, analyze, and share real-time business analytics easily. It captures and analyzes data from multiple sources to help make data-driven decisions.
Cloud-based business intelligence and analytics solution that helps users analyze data from business applications. It offers interactive drag-and-drop capabilities to create, filter, and share dashboards, SQL mode to communicate with databases, data layering, visualizations and charts, and data blending to combine disparate data sources and glean actionable insights quickly.
Enterprise-scale data integration platform with exceptional built-in ETL tools. Alooma offers a strong focus on rapid pipeline construction, data quality monitoring, error handling, protection against data loss, flexibility to write scripts to monitor, clean, and move data as needed, and much more.
Cloud-native automated data warehouse that makes it easy to integrate and manage an organization’s data. It has an extensive array of native data connectors, it provides automated data ingestion and scaling of multi-node databases, it includes an intuitive management dashboard and an in-browser SQL editor, and much more.
Cloud-based ETL solution and data integration service that connects to numerous data sources and automates the collection, detection, and preparation of data using an optimal relational schema.
17. Informatica Powercenter
On-premise ETL tool that provides seamless connectivity and integration with all types of data sources, an automated data validation, advanced data transformation that supports non-relational data, and a metadata-driven management approach.
18. Informatica MDM Reference 360
Cloud-based platform that has an end-to-end approach with embedded data integration, data quality, process management, and more.
Tool that automates workflows to create new code sets and performs accurate data mapping to eliminate barriers to data access.
It manages master data by standardizing, cleaning, and matching source data. It enforces business processes to enable data stewards to master data with feedback from analytics