Six Top Data Management Practices Every Organization Must Follow

By in ,
174
Six Top Data Management Practices Every Organization Must Follow

Storage silos in most traditional organizations are bursting open from the rapid evolution in big data. Most of these organizations are now concerned about data management practices in their organizations.

In the last decade or so, every industry from manufacturing to advertising has migrated to multichannel sourcing of data. This means each individual set of data now competes with every other set for analytical significance. Businesses can easily stretch out of their means of trying to fuel this process. Resultantly, very few companies can claim that they are making the best use of their data.

By all means, the answer lies in implementing a data management solution that is practical. Plus, it should improve the quality of the collected data. Moreover, it can also be a vital step toward solving productivity issues.

The focus is steadily shifting toward the production of well-analyzed, relevant and timely data. Such data allows businesses to make improved decisions and usher in substantial growth. Fitting in data management solutions in business could be challenging. And if you have not started yet, you might totally miss out on what’s actually covered in data management.

With a data management plan that is centered on specific business needs, every new asset in data will undergo extensive monitoring processes to make sure there are no security threats and data is kept safe. Here are some top data management principles and practices that will help your organization make the most of the available data assets.

Understand your business goals before data objectives

Data-Management-Practices-2

Over the next decade or so, the volume of data will snowball into a living data giant. In parts, this development will be propelled by the new digital devices that are constantly being added to systems and networks. The uninterrupted flow slows down data collected previously further down the silos as newer sets of data assume more importance.

Using data to understand and realize business goals is quite common as a practice. But a data would scientist would recommend that organizations keep referring to the business goals throughout the process of data planning. This helps companies identify the most important data sets and understand whether or not those need to be placed in a silo.

As an organization, you also need to consider how every dataset can impact the KPI that you would want to improve. Based on the goal you set, you will have to make a decision on what data you want to store. At the moment, most organizations do shoddy data management.  They store a lot of data without a well-defined purpose or store mechanism.

The best way to work around this is to know and decide how much data and associated technologies you will need to crack the goal.

Club AI and machine learning in data management

Data-Management-Practices-3

The more datasets an organization accrues, the more time it takes to conduct analysis and reporting on every one of them. With new techniques like artificial intelligence, the extraction levels on the collected datasets are all set to go deeper with machines getting contributing a bigger chunk in the analysis. Data companies are already championing inter-technology collaboration to better facilitate GDPR guidelines.

The other big factor in data management is big data. Given how big data has become in the past few years, artificial intelligence will be an even bigger factor in the months and years to follow. AI can deliver fast, economical and high-quality intelligence from ginormous sets of data. It is beyond impossible for humans to derive actionable insights from such data volumes.

With the onset of GDPR, almost any organization that dealing in significantly large volumes of data will need artificial intelligence. The major ways in which AI will help companies in better data keeping include:

  • The ability for consumers to check in and out of official communications
  • Supply consumers with reports on what data the company collects from them
  • Give consumers easy ways to delete all data the company has about them

Without artificial intelligence supplying the necessary technology, these processes will become heavily time-consuming for businesses.

Ensure the right people manage data

Data-Management-Practices-4

A good data strategy for a business starts with placing the best practices and principles in place. However, what you want to know is that success is a result of the right people managing data for your organization.

Start with planned data governance. Deriving maximum value from data is critical to any data strategy of a business. Perhaps, the first of many steps in data strategy is to include data governance as a principle. For one, this will make sure that the data being used in the business continues to stay of the highest quality throughout its lifecycle.

Data governance is a process in the evolution of new businesses. Since it’s based on integrity, usability, and availability, it allows for the whole industry to make use of the data. With big data and analytics, companies can improve security, reduce costs, ensure compliance, improve data quality and derive meaningful insight.

Implementing an enterprise-wide governance framework to reduce the cost of operation and risk associated in the subsequent projects.

Make data accessible

Data-Management-Practices-5

Data security is as important for an SME as it is for a Fortune 500 company. But in a mad bid to secure data, companies cannot afford to forget data, which might, in the long run, make it defunct altogether. Data needs to be stored securely, but without compromising on the accessibility for those who need the data. Imperatively, the same data should not be available to those who do not have the proper clearance.

Staying on the top of data access protocols is key to cope up with the rapid leaps into the digital age. Organizations must make sure that data is stored at places where relevant groups can have easy access to them. The age that is coming is more data-driven than we would think. At that, it is relevant that organizations are adequately prepared to extract data from dashboards. The message here is simple – silo data is not of any particular use to a company.

Defend cybersecurity threats

Data-Management-Practices-6

Most companies have an Incident Response Plan by now. But the common mistake that most companies end up making is to deviate from that plan. So first of all, there has to be a clear plan accentuated with decision points in times of crisis. That will let companies know if there is a legal requirement, good faith or regulation to find a breach which is either potential or realized.

To start with, an Incident Response Plan should be established before the occurrence of any major incident. The plan should include all the points that will help in recovery, eradication, containment and also supply with expert testimony.

Democratize data management 

Data-Management-Practices-7

Data management principles and practices must be kept up collectively by a business. Using a holistic method to work lets every member in the company to gain access to data infrastructure and create a way for better data management processes. Along with solid governance, this method can introduce successful master management of data as well. But for company-wide success, the integration must first happen within the company.

Data management practice aids in the study of data in the correct perspective to arrive at conclusions that align with business objectives. Now that organizations are hoarding lots and lots of data, the key is in classifying the data well and making a senior official in the company accountable for it.

Data democratization is desirable. There’s no question about that. However, it has surpassed desirability. With GDPR rolling into action faster than most would have imagined, someone within an organization has to take responsibility for the data of their users. Moreover, implementing stricter data guidelines will also ensure that companies are aware of the kind of data that flows through their organization.

If you follow these recommended data practices, you will be that much closer to making holistic use of data.

Futran Solutions specializes in delivering composite data management and analytics for small and medium enterprises. As applications of data management in business keep evolving, so do the resources that shoulder these needs within an organization. Speak to a Futran Data Analytics specialist today. Find out how we help you achieve your business and marketing objectives.

Leave a reply

Your email address will not be published. Required fields are marked *