Safe, secure, and effective data management is essential for developing, building, and deploying an enterprise-grade IT ecosystem for your business processes, operations, and applications. It provides analytical metrics and other vital data to help improve your strategic planning and decision-making and improve your overall enterprise security, among many other things.
Data management refers to the complex process of collecting, organizing, storing, and managing data within one business organization. This data helps a company cover all aspects of conducting their daily entrepreneurial activities, from security to customer interactions.
Data is among the most valuable assets that every modern-day business depends on for business growth, market expansion, and beating the competition. A company must be able to keep the data accessible, available, accurate, and secure.
That’s why data management involves several functions and operations to ensure the information in corporate systems is secure and up-to-date.
Why data management matters
Since data is the new currency in the age of the digital business, information has quickly become one of the most invaluable corporate assets. Some of the most common data management use cases include:
- Improving the process of decision-making;
- Doing market, pricing, and competition research and comparison;
- Analyzing business, marketing, and advertising performance;
- Reducing the cost of business operations;
- Optimizing business processes and workflows;
- Improving marketing campaigns;
- Increasing sales and revenue.
The new digital age of online businesses has brought a range of regulatory compliance regulations to modern businesses, including the California Consumer Privacy Act, GDPR, and similar data protection and privacy regulations. The number of internet users is increasing daily. They generate enormous amounts of data every day, and businesses invest quite an effort to capture that data.
However, that’s exactly the problem. Since businesses gather ever-larger volumes of data, the information comes in various formats that are virtually impossible to manage without having the proper data management system in place.
With that in mind, let’s talk about the most important aspects of data management to help you understand what the data management concept implies.
Various aspects of managing data
Since data management is quite a complex and tedious process, businesses use an array of techniques, tools, and technologies to handle different aspects of data management. Let’s review the most important ones.
Database management systems
One of the most popular aspects of managing data is developing enterprise-grade database management systems.
The most prevalent and effective type of DBMS is the relational system of database management. It manages your sensitive and essential business data by organizing it into tables with columns and rows, where each column and row contains specific database records.
This data management system eliminates data duplication and is considered the most effective solution for managing structured transaction data, including supporting all four transaction properties – durability, isolation, consistency, and atomicity.
Other types of DBMS technologies include viable solutions for managing various data workloads, such as:
- NoSQL databases (graph databases, wide column stores, key-value databases, and document databases) – perfect for storing semistructured and unstructured data such as application and server logs, network and internet clickstream records, sensor data, etc.;
- In-memory databases – top data management solution for improving I/O performance; ● Columnar databases – a perfect solution for analytics applications;
- Hierarchical databases – one of the core elements of NoSQL and relational systems;
- Managed cloud databases – top solution for both cloud-based and on-premises systems that manage database administration, configuration, and deployment.
Big data management
Since most big data ecosystems are built around open source technologies, they are perfect for various data deployments, such as managing and storing an array of data types, formats, etc. Modern-day big data systems are cloud-based as they can be easily deployed in the cloud environment.
Data warehouses are among the most reliable, safe, and secure data repositories that have two main functions – to safely store data and help manage analytics data. Even though data warehousing is somewhat a traditional data management technology, it’s still a widely used solution by countless businesses.
This data management method is based on either a columnar or relational database. Its main function is to structure and store data gathered from various operational systems for further categorization and analysis.
Some of the main use cases for data warehouses include:
- Enterprise reporting;
- BI querying;
- Inventory management;
- Key performance indicator management.
A data warehouse can help a business by allowing it to gather data across organizational business systems and store them safely in one easily accessible and secure place.
Some data lakes are upgraded versions of data warehouses designed to keep large quantities of big data for use in advanced analytics, machine learning, predictive modeling, and other advanced business applications.
Data modeling refers to the data science process of developing a range of physical, logical, analytical, and conceptual data models that are designed to complete various tasks such as:
- Mapping data workflows and sets for analysis and transaction processing; ● Documenting data in various forms (visual, graphs, charts, tables).
Some of the most popular data modeling methods include the development of data schematics, mappings, charts, and entity-relationship diagrams. While data modeling helps forecast various business-related events, it requires constant updating.
Creating and deploying an effective and well-designed data management system can help a business organization in various ways, ranging from gaining an advantage over competitors to improving decision-making and operational effectiveness.
The more a business invests in data management, the more it can make its operations more agile, effective, and scalable. Data management makes it easier to monitor trends and identify opportunities, as well as strengths and weaknesses within a business.
In addition, data management helps improve security by mitigating cyber threats and preventing data breaches. It allows a business to find and solve data privacy issues and stay in compliance with the latest regulatory requirements.