Data management is a process that includes collecting, validating, storing, protecting, and using data securely and efficiently. Data management helps an organization and its employee to optimize data usage under the regulations and policies. It helps them make decisions and take appropriate measures to maximize the benefit of the organization. Over the years, organizations are using Big Data to make business decisions and get insights into opportunities, trends, and customer behaviour to deliver impeccable customer service. As organizations primarily rely on intangible assets to create value, a robust data management strategy is becoming more important these days.
Current Data Management Systems (DMS)
It is imperative to devise an efficient way of managing data across a diverse data tier. A data management solution can be pretty helpful in achieving this. Built on data management platforms, DMS can include databases, data lakes and warehouses, big DMS, data analytics, and more.
Although database administrators (DBAs) use current tools to automate the traditional data management tasks, manual efforts are still required due to the size and complexity of most of the database deployments. This is one of the reasons why an error occurs. The key objective of a new data management technology is to reduce the need for manual data management.
Why Data Management Is Important?
Nowadays, organizations use data to make informed business decisions, optimize business operations, reduce costs, and improve marketing campaigns. Whatever it is, the primary objective is to generate revenue and gain profit. However, poor data management can be detrimental to an organization resulting in inconsistent data sets, incompatible data silos, and issues with the quality of the data. Such things limit an organization’s ability to run business intelligence (BI) and analytics applications.
Another reason why data management has been of utmost importance is due to the fact that businesses are required to abide by the increasing number of regulatory compliance requirements. These include data privacy and protection laws such as General Data Protection Regulation (GDPR) and the California Consumer Privacy Act (CCPA). Furthermore, various organizations/businesses including Paint Inspection Ltd, a leading paint inspection company are generating massive volumes and a wide variety of data types. Hence, with the lack of proper data management, these environments will be significantly challenging to navigate.
Best Practices Of Data Management
A comprehensive and well-thought-out-set of best practices are required to address the challenges of data management. Organizations with distributed data environments that include a diverse set of systems require a well-designed data governance program which is a vital component of effective data management strategies. Ensuring high-quality data is also crucial for an organization. Both users and business executives should ensure that their data needs are met and data quality issues are addressed properly.
Furthermore, the deployment of databases and other available data platforms needs proper approach when designing a data structure and selecting technologies. It is imperative for the associated staff to ensure that their implementation is suitable for the intended purpose. They should also ensure that the systems will deliver the data processing capabilities and analytics information required by an organization’s business operations.
It is a fact that better analytics is directly associated with data management best practices. Companies can optimize their Big Data by properly managing and preparing the data for analytics. Organizations and enterprises should make an effortless approach to access traditional and emerging data. They should be able to infuse quality into the existing business processes by scrubbing the data. Organizations can gather, sort, and store data with the help of data management platforms. Executives and marketers can get the most accurate business and customer information as the top-performing data management platforms can manage all of the data from all data sources in a centralised location.
Challenges Of Data Management
The fast-paced nature of business and the rapid growth of data are tow of the root causes of the challenges in data management. Organizations should ensure a proper keep up of more-effective data management tools due to the ever-expanding variety, and volume of data.
- Most of the companies are unaware of what data they have. A wide variety of sources like social media, smart devices, sensors, and video camera generate enormous amounts of data that gets collected and stored. However, they are of no use unless an organization knows what data it has, where it is located, and how to use it.
- With the expansion of their data tier, companies must maintain their performance levels. They need to constantly monitor the type of questions the database answers and change the indexes with the changes in queries, without making a negative impact on performance to maintain peak response times.
- Another important thing that organizations must meet is constantly changing compliance requirements. They must be able to review their data and identify anything that comes under amended requirements if any.
- Organizations don’t know how to repurpose data to put them to new uses. They must be able to process the data as mere collection and identification of data is of no use. The value of data is lost if it takes longer to convert them into what they need for analysis.
How Data Management And Data Management Platforms Benefit?
Whether structured or unstructured data, managing them is the first step, as these floods businesses daily. Organizations can harness the power of their data effectively through data management best practices, discussed above. They can also gain insights to make the data useful. More and more organizations are using data management platforms to use data analytics in effective ways like determining the actual reasons of marketing failure and business issues in real-time, customer experience personalization, value addition to customer interactions, enhancing customer engagement, and increasing customer loyalty.
Over the years, organizations are realizing the fact that data is a valuable asset which can be extremely helpful in making informed decisions, identifying trends, and taking appropriate actions before the competitors. They are actively looking for effective ways to derive value from data. By adopting an appropriate Data Management program, an organization can make a positive impact on the administration and use of data assets across every line of business.