Data management systems are no longer considered useful, but rather optional resources for decision makers. They now play a central role in the functioning and productivity of the organization. How a business collects and processes its data can mean the difference between profit and loss. Strong data management can even prove to be a competitive advantage in areas such as high technology.
The growing demand for actionable information has driven a corresponding evolution of our data platforms. The global data market is projected to be worth more than $77 billion by 2025.
Here’s a quick rundown of why and how your business needs to deploy data management systems.
What is data management?
Data management is the process of collecting, storing, processing, and accessing data. Data by itself is useless. But depending on how you purchase and use it, it can change your business processes.
Increasingly, businesses have a data management strategy to determine how they intend to use the data they have access to.
Data management includes a wide range of tasks and processes, all of which are performed by a data management system:
- Generate, update, and access data for a wide range of stakeholders.
- Store data locally or in cloud systems.
- Ensure reliable availability and recovery of stored data.
- Deploy it for use in business functions and interfaces.
- Ensuring data privacy and security.
To ensure the reliability of your data, it is useful to partner with a custom software company that can not only deliver software but also take full responsibility for your projects, covering the entire lifecycle: idea, design, delivery, and support.
Why is data management important?
In the digital world, most transactions and business decisions are made based on data. The only catch is that raw data is not actionable — at least not at scale. And as much as 80-90% of the data is unstructured or in a natural state.
Data management systems help you collect and process raw data to produce valuable information that you can use. When done correctly, it provides many benefits, including:
Improved visibility
First, data governance significantly improves visibility into your organization, including your assets, processes, and stakeholders. This allows people to quickly find reliable data to solve their queries and support their actions.
Process reliability
Data management helps you create standardized processes across all your functions and track their implementation. Warehouse management solutions are a great example of this. They allow you to know exactly how many items your warehouse can handle before it becomes full, allowing you to structure your logistics around this.
Business value
Data is essentially business capital. Let’s say you are an automobile manufacturer planning to enter a new market. A thorough analysis of consumer preferences, as determined by their purchasing habits and secondary research, can tell you which features and modifications are likely to prove popular and help you gain market share.
Digital transformation
Data is the basis of digital transformation processes. The technologies that influence and continue to shape industry and behavior are data-driven. Cloud, artificial intelligence, machine learning, blockchain, and more require timely and accurate data to provide value to their users.
Regulatory Compliance
Robust data governance is critical to ensuring compliance with local and global data security laws, such as the EU General Data Protection Regulation (GDPR), as well as industry- and company-specific privacy requirements.
Types of Data Management Systems
Data management systems include various platforms and components that allow you to control your data from start to finish. There are several different types of data management systems to choose from:
Database
Databases are often stored on a single computer system. They are a compilation of structured information, usually organized into a series of tables with rows and columns to make the data easier to view.
Data warehouses
A data warehouse is essentially a consolidated data store designed to support business intelligence functions such as reporting and analytics. It often includes a large amount of historical data from a variety of sources, including enterprise and transactional applications such as those used by point-of-sale systems.
Data lakes
A data lake is a system designed to store unstructured, semi-structured, and structured data. It serves as a way to organize large volumes of diverse data from a variety of sources. They are especially useful for businesses that want to engage in extensive data exploration and discovery.
Big Data Management Systems
As we continue to generate and process data at enormous speeds from multiple sources, we need new types of systems capable of processing this output. Big data management systems are designed specifically to handle all this information, including integrating it from different sources and analyzing it to produce valuable insights.
Therefore, these operations should be entrusted to professionals in this field from some data management company that has proven itself in the market.