Data management is securing, processing, and storing data collected and created by an organization. The data is used later for strategic decision-making to improve business outcomes.
Advancements in technology have led to great developments in artificial intelligence, hybrid cloud applications, IoT, and edge computing. All these developments have contributed to the exponential growth of organizations' data. They have also increased the complexities associated with data management. As a result, data management has become a major priority in most organizations.
Components of data management
Due to data management challenges, organizations have adopted solutions to unify and secure data. In addition, leaders in the IT department glean insights through data visualization tools and dashboards, making it possible to investigate complex challenges. All these operations are meant to elevate customer experience.
The following components are implemented to streamline strategies and operations of data management within an organization.
The type of data and its purpose often dictate the storage repository to be leveraged. That means the data warehousing facilities should have a defined schema that meets the particular data analytics requirements for the outputs. Data collected by the organization can be stored before or after it's processed.
In most cases, data requirements are directed and documented by the IT department in partnership with other stakeholders like outsourced data engineers. The structure of the data warehouse is usually organized as a relational system.
Data security means setting guardrails to protect all digital information from intruders. With the advancing technology, cyberattacks have become a huge concern, and there should be great scrutiny on the data practices to ensure customer data's protection. Clear strategies should be laid out to recover data in case it's lost to cyber criminals.
Data breaches can be costly and, in most cases, destroy the company's brand reputation. That is why security teams should invest heavily in leveraging encryption and other data security practices to safeguard the data and achieve operations management goals.
When raw data is ingested from different sources like mobile apps, forms, surveys, or from, it's then processed and loaded via disparate integration techniques like Extract, Load, and Transform. Over time ELT processes have improved greatly due to the emergence of disparate cloud platforms and the increasing demand for real-time data.
The data is filtered, aggregated, or merged during processing to ensure that it meets the requirements of the intended purpose. This could be a predictive machine learning algorithm or business intelligence dashboard.
Importance of data management
The foundation of information and the basis on which the management makes decisions is an important asset of every organization. Proper decision-making can only be achieved if the data is accurate, organized, and consistent. Below are the benefits of data management.
Leads to increased productivity
When data is managed effectively, its access gets easier, especially when dealing with large data organizations. The more organized the organization, the higher the productivity. The IT team members can do their work efficiently and produce better results by accessing data faster. It's through data management that organizations' goals are achieved without lots of hassles.
Every employee can easily understand the information being relayed and communicate it to the respective members. Whenever there is missing information due to the messages lost in transit, it can easily be traced and updated without many challenges.
The success of every organization depends on how smooth the operations are. Every organization's dream is to have seamless operations, which can only be achieved through data management. Data management determines how long an organization can take to respond to changes in trends.
If the organization takes too long to respond to these challenges, there is the likelihood that some of the processes will get complicated. And in this case, the organization risks falling behind. With great data management, you can respond to technological advancements and stay on the competitive edge.
Better decision making
Decisions made in every organization are based entirely on data management. If the data being ingested is inconsistent, the decisions will not be worth it. On the other hand, when everything to do with data management is done correctly, everyone in the organization knows what to look for exactly.
This drastically improves the quality of decisions you make for the whole organization. By nature, everyone has a different way of processing information but having a centralized system provides a framework for better decision-making. Therefore, the employees in the organization can plan, organize and make great insights from the data.
Data sharing and privacy
The organization's data should be highly protected from unauthorized access. Data management allows you to share data with only authorized users that have access to the database. Users with permission view and modify data as per the management guidelines.
As stated above, data breaches are costly, and customers can even sue the organization if their data is stolen. In case of any inconsistencies with the data, the management can easily question the authorized users about the events that caused them.
Eliminates data redundancy
Poor data management can lead to a lot of challenges. It can even affect the storage space allocated for the data as it can lead to the creation of duplicate files that will occupy extra space. Sometimes these multiple copies are stored in different storage locations, and it can be very difficult to resolve redundancy issues. If you try to solve these issues, you will require an additional workforce and space.
With data management, you will reduce these repetitions by integrating different files stored within the organization into a single database. The data in different locations is usually converted into a single database, and all the duplicates are deleted. Any change in the data or duplicate entries is reflected immediately and can be acted upon.
Data management reduces risks associated with data processing and provides accurate data for analysis. It helps optimize resources, contributing to better decision-making while keeping the business's regulations, policies, and rules in mind. To implement data management, you must ensure you implement the components mentioned above to benefit your organization.