How to Create a Modern Data Management Strategy [5 Key Steps]

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Data management strategy with Vaultastic

As the world moves on from a dark pandemic, there are a few positive takeaways from experience. One of those positives is how much technology has advanced in the past few years, especially in data. A recent article reported that 90% of the world’s data was generated between 2019 and February 2022. A stunning number that portrays how much of an essential asset data has become. 

Organizations revolve around data nowadays, but that does not mean they are adept at handling data. The quick increase in data generation and storage in the past two years has meant that data management strategies still haven’t caught up. 

Unstructured, raw data fragmented across various platforms is unsuitable to meet modern enterprise needs of long-term safe protection, rapid discovery, and easy recovery.

Enter Data Management. The objective of a modern data management strategy is to transform or refine raw data into a valuable resource. 

But as mentioned earlier, technology is always on the move, and as technology advances, it brings about contemporary issues that require modern solutions. And this blog will delve into modern data management, its benefits, and how to create a modern data management strategy. 

What is Modern Data Management?

Organizations demand more versatility and compatibility in storing and managing vast data. The data is collected, processed, analyzed, and refined from various platforms and sources. 

Cloud computing, robust data integration tools, multi-layered security systems, and the implementation of machine learning are all excellent examples of modern solutions that deal with the ever-changing data management loopholes.

The ability to handle data collected from newer sources with cutting-edge technology differentiates data management from modern data management. 

Therefore, modern data management is upgrading and adopting new technologies to handle the constant developments related to data storage and management regulations.

Modern data management is a comprehensive, multi-disciplinary approach involving current data analytic and technological tools and several thorough processes to streamline the massive amounts of data collected and aid in other complex data management tasks. 

Related: Key Components of Modern Enterprise Data Management

Why do you need Modern Data Management?

The fundamental basis of modern data management revolves around implementing new-age technology and tools to get a grasp on data that is increasingly becoming complex and difficult to process. 

Earlier data management processes and architectures like big data management and data warehousing could not cope with the massive amounts of data and the complicated nature of collecting the data. 

There is a multiplication in the number of sources and platforms like social media where you can mine data compared to 5 years ago. 

These complications are why organizations shift to modern data management strategy and architecture. 

By 2025, reports indicate that the world will generate about 463 exabytes of data. With thousands of new devices being connected to the internet daily, it is safe to say that data will become ever more valuable. 

This growth projection calls for solid and comprehensive modern data management strategies. 

How to create a Modern Data Management Strategy [5 Key Steps]

Modern data management includes several multi-faceted processes, but more importantly, it is an ongoing process once operations begin. Therefore, getting the strategy close to perfect is of utmost importance. 

Here are five critical procedural steps to help build an effective strategy:

1. Identify and realign business objectives related to data

The first and most significant step warrants a successful modern data management program: re-exploring the organization’s needs. 

  • What are the organization’s goals? 
  • How will this data help us achieve our goals?
  • Is the identifying and realigning related to it wanting to understand customers better, or 
  • Better understand the marketing landscape, or 
  • Is it to innovate, establish a product/service, or even deal with internal organizational affairs? 

Going over these factors will help you better create a data management strategy. This understanding is the basis for determining which tools, processes, and technologies align perfectly with your organization’s objectives.

2. Build sustainable but effective data processes

Once you know your organization’s goals and objectives, the next step is building a framework for the various data management activities. Also known as master data management strategy, this is where you will discuss data as a whole – 

  • What happens when data is received? 
  • From where is it collected? 
  • Where is it stored, analyzed, and distributed? 

You will later implement these processes in your modern data management architecture. This streamlined link between these processes massively helps handle vast amounts of data consistently.

3. Look for and adopt the right technology

In modern data management, identifying the right technology is paramount. Getting this right can give you a competitive edge.

As mentioned earlier, modern data management is all about adopting newer tools that ensure that your data management is not limited but flexible and can adapt to constant advancements in technology. 

Consider these six factors while choosing your data management platform:

  1. Is your data automatically captured and protected centrally?
  2. Does your data management platform preserve your information in an operational infrastructure separate from your primary data sources?
  3. Is your information in the data management solution immutable and tamper-proof?
  4. Is your data archive preserved in highly durable storage?
  5. Can you find and extract data easily and quickly?
  6. Does your data management platform optimize costs along the entire data lifecycle?

Related: 6 signs of an effective data management strategy.

Therefore, it is vital to research the latest technology comprehensively and look for the perfect tools that work with your organization’s goals and data processing framework.

Microsoft 365
Salesforce
Microsoft Onedrive
SendGrid
Freshdesk
Google Workspace

Vaultastic - centralized, and agile information archival

Providing protection, visibility, and agility for business-critical data to ensure business continuity and manage compliance and change

4. Adhering to stringent regulations and data governance laws

It is important to ensure that your organization complies with industry regulations and government laws. 

Over the past few years, industry regulators have been getting stricter, and governments have passed various laws protecting privacy and data.

Establishing data governance in your organization means taking responsibility and accountability for proper data usage and storage in alignment with regulations and laws. 

This alignment helps formulate a data quality management strategy and covers other important aspects like security and compliance. 

5. Build a Strong Team

However much we talk about data management automation, there is still a need for a robust knowledgeable group of experts who can overlook the functioning of the processes. 

While adopting newer tools and technologies, providing the proper training to your employees becomes a priority. A successful modern data management program is when every employee understands the strategy, where they fit in it, their role, and how to execute it successfully. 

Related: Five data management best practices

Benefits of Modern Data Management

Now that we have looked into how to create a modern data management strategy, here are some additional benefits of encouraging your organization to invest in a current data management system –

  1. Modern data management improves operational effectiveness, productivity, and decision-making.
  2. A seamless modern data management system ensures smooth and streamlined functioning of data processes. The improved processes enable smoother transactions with customers and partners and help you adopt ongoing trends, keeping you a step ahead of competitors.
  3. Reduces the risk of data loss. An excellent modern data management architecture includes a cloud data management strategy and a robust backup system that allows you to retrieve any lost data quickly.  
  4. With the implementation of data governance, you can handle the security and privacy of data well. It eliminates the chances of data breaches and regulatory compliance issues.
  5. A modern data management platform is flexible and can adapt to evolving situations quickly.
  6. A modern data management solution deploys strategies to optimize costs even as your data volume grows.

Summary

Data will continue to be a significant resource in the foreseeable future. As multitudes of devices connect to the internet, data generated would only explode in unscalable numbers. But in all of this, there is a catch – you don’t need all of the world’s data. 

You need a system that minimizes data relevant to your organization and transforms it into a valuable asset that brings success to your organization. 

A modern data management system is a must for all organizations who want to continue growing in the future and manage the growing data effectively. They can use the above-given strategies to create their system, or better and easier yet; they can partner with data management experts like Vaultastic. 

Vaultastic is one of the world’s most prominent data management and archival service providers. From archiving data to creating agile data management systems, Vaultastic can provide you with the right solutions for your modern data management needs. Start by taking a free trial of our system, and you will realize that Vaultastic is the right partner to help you with the right modern data management strategy.

About Vaultastic

Vaultastic’s groundbreaking information protection and data lifecycle management platform offers centralized archival & supervisory controls, quick discovery, and data activation for easing compliance management.

The key feature is its on-demand data management service, automatic storage management, atomized discovery, and activation, delivering cost savings of up to 60 percent over other methods.
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