Database Management System- What is its role and importance?

Sales, Technology | 5 minutes to read

25th Sep, 2019

In an exclusive conversation between Snehashish Bhattacharjee, Global CEO, Denave and PCQuest, Snehashish shares his perspective on the criticality of intelligent database management for business.

Please elaborate on the significance of the Database Management System and its impact on the business.

There is a constant change in the world of data. It is evolving every second that in turn has created a completely new dimension of growth and challenges for companies around the globe. Today, by accurately recording data, updating and tracking them efficiently, companies can solve their challenges and also utilise its immense potential to fastrack their business growth.

Technology is helping us understand and predict every facet of a customer’s online/offline interaction with a brand, and businesses can leverage that data to customise and curate targeted marketing campaigns. A  Database Management system becomes crucial for the same reason.

The overall impacts can be seen as

  • An efficient Database management helps in categorising and structuring data and optimizing business operations
  • It facilitates strategic and data-driven insights to accelerate revenue engine, via increasing net new customer acquisitions and generating maximum sales impact.
  • With the database management system becomes crucial in optimising business’s efforts in avoiding legal liabilities, failure to meet regulations and eliminating risks in general.

What are the challenges in the path of an effective Database Management?

Organisations are struggling to gain competitive advantage in today’s digital economy. It requires organisations to provide employees, partners and customers with secure access to critical enterprise system and applications anytime/anywhere. But failure to effectively manage their data can end up costing the organisations in lost productivity and missed opportunities. Probably, data management challenges can unavoidably arise pertaining to:

  • Storing and leveraging huge volumes of data
  • Ensuring data cleanliness, accuracy and contactability
  • Complying with strict regulatory mandates, forcing modern security practices and access control measures

These challenges often render the database ineffective that may further plague businesses leading to long-term complexities. Organisations rely on data to assist their marketing, sales and customer service efforts and if that data is inaccurate they are bound to waste time chasing the leads that don’t even exist.

Share some tips on intelligent database management

Database management is beyond backing up files or storing data in the cloud. These are fundamental activities when we consider database. Moving beyond it is important to ensure that the data is properly protected and easily retrievable.

Sometimes when things goes in a wrong direction, it’s not always the people or the technology at fault, it can also be the processes. So, if you have the right people in place, the processes are transparent and are using the right technology, you can be on the road to success.

We can consider some pointers while endeavouring to put in place a smooth and error-free database management process.

Make data entry guidelines This is all about documenting the processes. Data entry guidelines tell us what type of data is being entered into any given field (which means – if you are entering an address, are you spelling out “street” or “St.”). This provides consistency in data entering and also make it easy to find and correctly identify files, prevent version control problems when working on files collaboratively amongst others.

Automation of information updates Manual data entry is a cumbersome task for any organisation. Also, it may lead to the lack of data accuracy. Such monotonous job further leads to the loss of employees’ significant time. With the automation of data updates, users can benefit from the process simplification and ease of operations.

Ensure Security at all levels There is a need to have multi-tier security in data management. You have to ensure that database is secured at every level so that not everyone can access it. There must be sturdy network security and the systems used to store the data should also be robust enough to secure against any ingrown or external threats of any form.

Keep your data up to date You need to understand that, as soon as data goes into your system it becomes out of date. People die, lose jobs, and change addresses. Therefore, try and keep your data as up to date as possible for accurate information.

Provide appropriate Training Training is an important aspect of people management. It must be provided to the new staff and also as a refresher later on to better understand the working process, to minimize chances of incorrect data entry

All in all, data integrity, beyond doubt, is considered as the cornerstone of marketing campaigns. Every company’s decisions, both operational as well as strategic, are based on the information collected from data. Probably, without the right data or proper management techniques in place, a business can be at risk of losing money, time wastage and potentially jeopardizing customer relationships. Therefore, it is important to properly manage database to enables companies to make strategic business decisions confidently, that positively impact business performance.

What does the future hold for intelligent database management?

Disruptive database management have pushed organisations to innovate to keep pace with changing market trends and competition. This also helps the businesses to stay relevant to the changing times.

Thanks to advances in computational powers, reduction in computing costs and the rise of big data, artificial intelligence is playing a critical role in the success of the modern organisation. More tasks that were earlier handled by data management professionals are now being tackled by intelligent machines.

With the implementation of technology solutions on data management, some changes that are predicted

  • Data as a service: Data as a service (DaaS), will provides access to all forms of data across the network through a standardized service layer. It is seen as the most promising development by some industry leaders. To effectively leverage data for competitive advantage, this fundamental technology is required to the solutions for enterprises to organize and access their data.
  • Data Governance Tools: A well-designed data governance structure will have an easy-to-use interface to encourage self-service data preparation while also having industry-proven data quality functions built in. It will empower the analytical community to access and use all data, in its original form, and validated for their analytical processes.
  • Real Time streaming: Real-time enterprise is bringing about a new generation of solutions that are geared to improving organizations’ abilities to sense and respond to opportunities or issues. In coming years it will make it easy to democratize and liberate data access to more users, from data scientists to business users.
  • Augmented Intelligence: Augmented intelligence is becoming a part of leading analytics platforms. Probably it will help in addressing the skills deficiencies faced with artificial intelligence development. Analytics platforms when incorporated with augmented intelligence will help in closing this gap and will change the way enterprises can compete with data.
  • Containers: Containers are those portable environment where applications, data dependencies and runtimes are housed. Currently they are creating a positive impact on enterprises’ ability to compete on data. With the continuous emergence of container orchestration and solutions such as Kubernetes containerisation will be highly strategic to optimise storage, security and networking.

In the coming years, data scientists will develop databases management system that will make easier to utilize all data in real time. This will also fuel the need for data analysts to come up with more complex computation and forecasts. Consequently, the need for future database management system will spark the emergence of new data technologies.

This article was originally published here.

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