The key business benefits of effective data management for the majority of our Executive Horizons survey respondents are “a greater understanding of their customers and the ability to target them more effectively” and “the ability to adapt products, services and business models to the changing needs and expectations of customers.”
The more customer insight you have, the easier it is to engage new audiences and connect with potential consumers. Being able to streamline and capitalize on the wealth of data available can therefore help organizations make more informed business decisions.
One company that has succeeded in gaining customer insight in order to create more targeted campaigns is Netflix. The video-on-demand service, which has 100 million subscribers, uses viewers' past search and watch data to suggest the next movie they should see. This type of data targeting can give companies real competitive advantage in highly competitive markets.
Effective data management can also help companies anticipate potential operational and reputational risks, before it is too late. In industries such as the financial sector, the ability to capitalize on data to identify, measure, monitor and manage risk is crucial. Singapore-based UOB Bank, for example, has developed a sophisticated data management system that can calculate value-at-risk in just a few minutes.
The ability to harness advances in technology and use data effectively will become even more critical in the years to come. Ultimately, companies that see data as a strategic asset will thrive, while businesses that ignore the data revolution run the risk of being left behind.
Managing Data of your company in an effective manner is one of the most important things that most of the companies almost forget to take care of and which is why they incur a huge loss.
Thus, if you are running an organization where you have to deal with a large set of data then it becomes important to manage your data effectively. Let’s have a look at the benefits of managing data effectively.
1. ) Redundancy Elimination or Elimination of repetition: Data Redundancy occurs when the same data set is stored in two or more places. It may not seem like a big deal until multiple data sets pile up more than once, taking up gigabytes of storage space on your servers. Managing duplicate data when your servers are already loaded can be a grueling process.
Common problems facing big companies and public bodies include data duplication. There is also the matter of outdated data providing users and consumers with poor quality experiences. In the healthcare industry, in particular, this could prove to be disastrous.
By managing the data effectively, we can reduce the redundancy in the data. The redundancies are bound to occur in the data if a large set of data is involved, and here comes the job of data management that helps in eliminating the redundancy in the data. Therefore, if you are running. a large organization, then the need of Data Management arises.
2.) Interpretation and Effective Data Analysis: Data interpretation refers to the implementation of processes through which data is reviewed for the purpose of arriving at an informed conclusion. The interpretation of data assigns a meaning to the information analyzed and determines its signification and implications. Similar & duplicate data can create a lot of problems for your business, and become fatal in some of the cases. Through data management, we can get a smart and decision-enabling data analysis, which is crucial.
3.) Data Consistency and integrity: Integrity means that the data is correct. Consistency means that the data format is correct, or that the data is correct in relation to other data. Data management guarantees consistency of data, which makes working with it easier as it prunes confusion, redundancy and creates easier and consistent workflow.
4.) Flexibility and authenticity: Data Flexibility is higher in the MDM compared to the other data management technique.
More Flexibility = More Scope for Analysis : Companies may benefit from a more flexible platform, offering you access to historical data as well as current numbers.
More Flexibility = More Scalability : It may be an obvious point to make, but scalable Data Management is immediately scalable. Data in the value of up to 2.5 quintillion bytes is generated every day. Further research shows that data storage will need to make room for more than 44 ZB worldwide. A ZB is a zettabyte. For scale, a single zettabyte equates to approximately a sextillion bytes. This is a truly incredible number, and if statistics are worth believing, the numbers are getting bigger. Therefore, corporate Data Management must be scalable.
More Flexibility Now = More Flexibility Later : A flexible Data Management plan will, therefore, adapt automatically to changing demands. Even if tastes and usage patterns change drastically in the years to come, companies with data lakes will be ready.
Some commentators believe that fighting change is a quick route towards obsolescence. Therefore, it may be in the best interests of global companies and organizations to instead “meet” change. This could be a key reason why artificial intelligence, for example, appeals to 90 percent of business investors. AI is actively helping to automate and auto-scale Data Management for the years ahead.
Keeping Data Clear and Flexible : Data Quality relies on accuracy as well as flexibility. We are always discussing ways in which data cleaning and management shifts are helping companies meet new demands. Big data is not something to fear. In fact, many agree that its growth is inevitable.
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