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The WWW Of Data Management

Data management refers to the process of organizing, storing, protecting, and maintaining data in a secure and efficient manner. It involves several aspects, including data collection, entry, storage, processing, retrieval, and disposal.

Effective data management is essential for businesses and organizations to make informed decisions, manage their operations efficiently

Today, businesses rely on data more than ever before. Not just data that they acquire through transactions with consumers and other businesses, but data they generate themselves. This can come from applications, sensors, third-party data suppliers, machinery, and even from products sold to, or implemented for customers.

In many cases, companies can actually end up with more data than they know what to do with. Moving it around and managing it can be impossible when you are drowning in data. Many companies struggle to keep their head above water, never mind move to a place where they are more data-driven and gaining true insights from that data. According to a Tableau white paper from May 2021, 83% of CEOs want their companies to be more data-driven, yet 70% of departments state they don’t have access to data. It is easy to see how this can be a huge source of frustration for many companies.

Now more than ever before, companies need to think about how they manage data and make sure they have a data management strategy in place that ensures this is done effectively and securely.

Thanks to a host of data management solutions available on the market today, businesses can become veritable data-driven companies capable of tackling present and future challenges, while also ensuring information remains secure.

What is Data Management?

At its heart, data management makes possible the collecting, updating and sharing of company information and data in a secure and controlled way. It is an essential strategic activity that simplifies the task of working with data for both small and large businesses. Until a few years ago, companies based their business choices on perceptions and previous experience. Now they can rely on a set of processes, policies and metrics through data management to form a single version of the truth, giving them reliable data that can be used to help them achieve their business goals and improve performance.

Well-implemented and structured data management can not only help achieve business goals. It can help identify and manage the governance, regulatory and compliance risks that a company might face, making those processes more efficient and secure.

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Why is a Data Management strategy so important?

Data is an extremely flexible and versatile strategic asset that can be used, moved and shared by different applications and company units in an autonomous and independent way. However, its flexibility must be optimally managed in order to benefit from all the advantages, while limiting and mitigating risks as mentioned above. Software can play a huge role in this, but a company also needs to define a strategy for how it will approach managing its data in order to select the most appropriate data management solution.

Today’s modern data management solutions are the culmination of a lengthy evolution that has led to the integration of technologies such as Internet of Things (IoT), Big Data platforms and the Cloud. In recent years, artificial intelligence and machine learning have also become an increasingly important part of any data management solution. This is because they allow companies to find patterns and relationships in increasingly large quantities of data, in a simple and rapid way, through highly user-friendly interfaces.

What does an implemented solution look like?

So, what should you expect to get from a modern data management solution? Here are our thoughts on some things that should be on your checklist regardless of the solution you choose:

  • User-friendly interface: Simple and intuitive interfaces matter because they make it possible for users to interact with data in an effective way and visual way. That is how your users will get the most from it and explore data in new ways. Whether they are searching for information or trying to conduct analysis, a graphical interface enables operators and uninitiated colleagues alike to execute operations with ease and at speed.
  • End-user-centric approach: Many traditional data management solutions are not designed with end users in mind and tend to be entirely focused on IT managers or admins. Modern solutions focused on the end user deliver unbeatable scalability within a self-service environment, because they are designed for the end user, or data owners, to share some of the responsibilities traditionally borne by administrators and IT departments alone.
  • Better productivity: Effective data management solutions help teams to boost their productivity by pooling information and granting access to it through a self-service interface. This reduces time wasted searching, and sharing (multiple copies of) data sets, with all teams able to reach the information they need in one place – as a single version of the truth. Working with these real-time data sets means that everyone is singing from the same hymn sheet and not using different versions of data, which may lead to poor decisions and outcomes.
  • Optimisation of costs and processes: A good system will help you cut the costs of downtime or excessively complex decision-making processes. This is crucial for any company operating in a competitive market, insofar as lengthy delays in making decisions or agility in executing them may undermine production, brand reputation or slow time to market.
  • Control over data policy: A good modern data management solution will enable a company to reinforce the protection of its data, while also reducing the risks of criminal acts or internal errors. This will be baked in, so that protecting data does not become a time-consuming and painful overhead for staff or IT departments.
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When should data management be implemented?

Data management should be implemented as soon as data is collected and throughout the data lifecycle. This means that data management should begin at the point of data entry and continue through processing, storage, retrieval, and disposal. It is also important to periodically review and update data management practices to ensure they are current and effective.

In today’s digital age, where organizations collect and store vast amounts of data, data management is essential to ensure that this data is properly stored, managed, and utilized to meet business goals and regulatory requirements. Effective data management practices

Strategy is the key

A solid data management strategy is a must in today’s quest to become a truly data-driven company, through the definition of resilient and smart practices. This transition to embracing data is an essential rite of passage that will rely on experienced technology partners and cutting-edge solutions, but fundamentally a strategy built around a strong corporate data culture is the key to success if a company is to truly benefit from the data on which it already sits.

Source: itbrief

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