Every day, we produce an almost unbelievable amount of data (328.77 quintillion bytes!) as nearly every aspect of our lives helps generate data, from data collected by the James Webb telescope to the images you share in Telegram. Nowadays, data is so heavily involved in our day-to-day lives that it’s becoming a critical and valuable resource. In fact, many think of data as the new capital. In business, enterprise data management tools are crucial to the smooth running of any organization.

Businesses in today's highly interconnected global economies have the challenge of deciphering data and identifying relevancy in the noise of systems and technologies. Yet, data is useless without a solid strategy, governance, and data management model to put it to good use across supply chains, employee networks, customer and partner ecosystems, and more.

But where does its value come from? In short, the value comes from the insights we glean from data by cleaning, processing, manipulating, and analyzing data to extract the potential that lies within. Cue your data management solutions to help maximize the value of data and transform it into insights. 

What is Data Management?

Data management, as defined by Dataversity, is “a comprehensive collection of practices, concepts, procedures, processes, and a wide range of accompanying systems that allow for an organization to gain control of its data resources. Data Management as an overall practice is involved with the entire lifecycle of a given data asset from its original creation point to its final retirement, how it progresses and changes throughout its lifetime through the internal (and external) data streams of an enterprise.”

Data management products are widely known in the business world; many leading companies, such as IBM, Oracle, Amazon, Microsoft, Google, and Dell, created a set of data management tools to satisfy all client requirements. These products are flexible for each business, allowing them to build a chain of information processing based on the company's data.

In essence, data management aims to simplify the optimization of data used to propel decision-making processes in an organization by collecting, maintaining, and using data in a secure, efficient, and cost-effective way.

What are Data Management Tools?

Data management tools are essential for establishing, monitoring, and optimizing data practices within an organization. They structure and streamline data efficiently, ensuring high levels of effectiveness.

These tools play a vital role in upholding data privacy and security while eliminating redundant data. Successful data management involves a blend of software tools and best practices to manage data resources effectively.

Modern businesses require data management services to efficiently handle data, whether integrated into a data management platform, accessible in the cloud, or in open-source formats.

Role of Information Systems in Data Management

Together, information systems and data management help tackle the challenges of Big Data, real-time analytics, data modeling, and the overall smart use of information. The emergence of large, diverse, and publicly available data poses the challenge of using the best methods that lead to the effective use of information systems, which is imperative to develop a holistic view of information.

Information systems and data management govern the two chief elements that are the pillars upon which they are built: data and information. In a previous article, we discussed the key differences between data and information and the unique connection they share. In essence, data is meaningless, but once it is processed, interpreted, formatted, and organized, it becomes information as value is extracted with a specific goal and purpose.

Massive amounts of data require a powerful data management and information system in place in order to process and analyze it to glean value and derive information that leads to smarter business decisions.

Types of Data Management Products

There are many benefits to using effective data management tools, and more and more of them are coming to the market. These are some of the most popular types of data management tools:

• Product Information Management (PIM). Ideal for manufacturers and retailers, PIM tools centralize and automate the management of product information across various sales channels, supply chains, and more.
• Master Data Management (MDM). MDM tools are designed to handle core business data, such as customer information, employee details, and operational data, ensuring consistency and quality through data cleansing, centralization, and synchronization.
• Data Modeling. Tools in this category help adapt data for storage by creating conceptual models and defining rules for data consistency and quality.
• Data Warehouse (DW). DW tools provide storage solutions for data but do not include specialized data management processes. They are dedicated to data storage and are often linked to existing hardware. Other processes like data quality analysis, metadata management, and data security may require separate tools.

Case in Point: Data Analytics Platform for Employment Background Screening

Data Management Tools

Traditional data management tools work specifically on the client databases and on-premises computing data centers on the client’s facilities. In contrast, the new data management tools work in the cloud. This allows you to significantly save on infrastructure and quickly adapt to changes in business requirements. For example, increase the amount of accumulated data, accelerate the development of new data processing, maintain IT infrastructure, and always have access to cloud-based tools.

Here’s a list of the most prominent data management tools on the market.

1. Oracle Data Management Suite

Oracle Data Management Suite is a 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.

Pros:

• Robust security measures
• Wide integration options
• Extensive support resources

Cons:

• Complexity of setup
• Customization limitations

Price: $6+ per GB per month

2. SAP Data Management

An 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. SAP Data Management 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.

Pros:

• Robust security features
• Highly scalable
• Simple data management and data migration

Cons:

• Complicated deployment
• Difficult to navigate

Price: Available on request

3. IBM Infosphere Master Data Management Server

IBM Infosphere Master Data Management Server is 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.

Pros:

• Robust data integration capabilities
• Critical master data centralization
• Data consistency and accuracy

Cons:

• Costly for small companies
• Requires technical expertise for implementation and setup

Price: Available on request

4. Microsoft Master Data Services

Microsoft Master Data Services 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 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 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 code-free by integrating data sources from more than 80 natively-built and maintenance-free connectors.

Pros:

• Powerful analytics and machine learning capabilities
• Seamless integration with other Microsoft products
• High availability and global scalability for data

Cons:

• Cost considerations
• Dependence on Microsoft technologies

Price: Based on custom quote

Microsoft SQL Server SSIS is a platform for building enterprise-level data integration and data transformation 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 various 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.

Pros:

• Comprehensive data management features
• Robust security measures
• Seamless integration with other Microsoft products

Cons:

• Higher licensing costs
• Limited scalability for huge data sets

Price: $0.592/hour+

Microsoft Power BI 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.

Pros:

• Many visualizations and customization options
• Support for multiple data sources and formats
• Large Power BI community

Cons:

• Complexity and substantial learning curve
• Lack of localization

Price: $9.99+ per user per month

5. Dell Boomi

Dell Boomi is an 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. 

Pros:

• Comprehensive data integration
• Visual interface for designing data workflows
• Real-time data monitoring

Cons:

• Complexity in setting up
• Requires technical expertise for advanced data mapping

Price: Based on custom quote

6. Talend

Single, open platform for data integration, data management, enterprise application integration, data quality, cloud storage, and Big Data across cloud and on-premise environments. Talend helps transform data into business insights to help companies make real-time decisions and become data-driven.

Pros:

• Intuitive interface
• Swift installation and deployment
• Custom code writing feature

Cons:

• Poor technical support 
• Error messages aren't intuitive, making it difficult to debug processes.

Price: Based on custom quote, there is a free trial

7. Tableau

Interactive data visualization solution that helps users see and understand data. Tableau helps simplify raw data into an easily understandable format for smart data analysis. Visualizations are created through dashboards and worksheets through key features that include data blending, real-time analysis, and data collaboration.

Pros:

• Mobile-friendly
• High performance
• Ease of use

Cons:

• No automatic refreshing of reports:
• Poor versioning

Price: $75+ per user per month

8. 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 can handle the scale, agility, and flexibility required to combine different types of data and analytics approaches to gain deeper insights. Amazon Web Services provides a comprehensive set of services to move, store, and analyze data.

Pros:

• Ability to process and analyze data in real-time
• Seamless integration with other AWS services
• Robust security features to protect data

Cons:

• Complexity in setup and management
• Vendor lock-in risk

Price: Based on custom quote

9. Google Cloud - Big Data analytics

Google Cloud - Big Data analytics is a 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.

Pros:

• Strong security measures
• Robust networking capabilities
• Flexibility

Cons:

• Limited availability of some services in certain regions
• Requires technical expertise for setup

Price: Based on custom quote

There are also a number of emerging data management tools from relatively small vendors that are worth mentioning: 

10. Looker BI

Business intelligence software and Big Data analytics platform that helps users explore, analyze, and share real-time business analytics easily. Looker BI captures and analyzes data from multiple sources to help make data-driven decisions.

Pros:

• Easy data filtering and navigation
• Simple integration
• Great user interface

Cons:

• Low speed
• Poor visualization

Price: Available on request, there is a free trial

11. Panoply

Cloud-native automated data warehouse that makes it easy to integrate and manage an organization’s data. Panoply has an extensive array of native data connectors. It provides automated data ingestion and scaling of multi-node databases. The solution includes an intuitive management dashboard, an in-browser SQL editor, and more.

Pros:

• Simple data integration
• Automated data modeling
• Query speed

Cons:

• Lack of built-in visualization tools
• Limited number of connectors

Price: $199+ per month

12. Informatica Powercenter

Informatica Powercenter is on-premise ETL tool that provides seamless connectivity and integration with all data sources, automated data validation, advanced data transformation that supports non-relational data, and a metadata-driven management approach. 

Pros:

• Seamless data integration
• Streamlined development process
• User-friendly interface

Cons:

• Complex installation and configuration
• Limited integration capabilities

Price: Based on custom quote

13. Informatica MDM Reference 360

Informatica MDM Reference 360 is cloud-based platform with an end-to-end approach with embedded data integration, data quality, process management, and more.

Pros:

• Easy to integrate
• Highly scalable
• Reliable

Cons:

• Time-consuming initialization
• Poor user interface

Price: Based on custom quote, there is a free trial

14. Collibra

Collibra automates workflows to create new code sets and performs accurate data mapping to eliminate barriers to data access.

Pros:

• Flexible
• Out-of-the-box metrics
• Data Lineage and traceability

Cons:

• Poor user interface

Price: Available on request, there is a free trial

15. Profisee

Profisee 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.

Pros:

• Streamlines data management
• Saves time
• Flexible

Cons:

• Poor customer support
• Difficult integration

Price: Based on custom quote

Realize Your Data Management Strategies With Svitla

In this article, we have presented the top data management tools available. Of course, this is not a complete list of available solutions, but we have described the leading and most popular data management tools. If you need to use some other tools for data management then you can navigate based on the proposed solutions and choose the one that will be acceptable for your business.

We’ve said it before and we’ll say it again, the future is data-driven, so it is critical and vital to build, develop, and deploy a comprehensive data management strategy that addresses your company’s needs in terms of gaining value from data capital.

At Svitla Systems, we have numerous years of experience under our belt with evident successful results for our clients in regard to comprehensive information systems and data management. Thus, we understand the intricacies of constructively managing data and dealing with the numerous emerging and well-established tools available in the technology ecosystem to effectively harness the inherent value of data and derive valuable insights and intelligence from it.

With experts in our ranks who are clearly accomplished in an arsenal of data management tools, we are sure to be your one-stop partner solution to orchestrate and realize your data management strategies. For more information about how we can help you with your data management projects, contact us and we will be glad to give you more details.