By clicking “Accept”, you agree to the storing of cookies on your device to enhance site navigation, analyze site usage, and assist in our marketing efforts. View our Privacy Policy for more information.
Top Trends in Data Management: 2023

Top Trends in Data Management: 2023

Top Trends in Data Management: 2023

June 10, 2021

Data is the new gold! This might just be the truest statement of Industrial revolution 4.0! Data management has become pivotal to almost every business today and is being generated at a rate that traditional technologies cannot keep up with! This has rendered Data Management one of the most formidable business differentiators today.
Enter : The modern-day savior, Artificial Intelligence (AI), powering itself with tools like machine learning (ML), natural language processing (NLP), cloud computing etc.

Here are the most important prevalent and emerging trends in Data Management  –  

Data Management Trends

1. Data Processing & Analysis Automation

Data extraction being the 1st step of data management poses many challenges. However, today, we see organizations building tools to crawl, sync and integrate apps and platforms, bundling different formats of data(including real-time). This automation has expedited the decision making process and shrunk time-to-action. AI and ML along with Business Intelligence(BI) technology are key enablers of this trend. IDC estimates that by 2025 nearly 30% of all generated data will be real-time compared with 15% in 2017.

2. Unstructured Data > Structured Data

Data until recently meant structured data. However, the exponential growth of communication platforms has proven that unstructured data shadows structured data. Managing unstructured data is a bigger challenge, since it comes in different formats and potentially has more privacy and security concerns.

3. Data Catalogues

Powered by ML, this technology enhances the search function by tagging and scanning data, eventually enabling Dynamic Search. Organizations can leverage this technology to enhance data accessibility and discoverability, ultimately driving effective data management.

4. Augmented Analytics (AA)

Augmented analytics uses technologies like AI, ML and natural NLP to assist with data processing and insight generation to augment how people explore and analyze data reducing data management tasks significantly. Gartner, Inc. predicts that by 2022, AA will reduce data management tasks by 45%. The AA market is projected to grow by about $18.4 billion globally in 2021.

5. Natural Language Processing (NLP)

NLP enables computers to understand human language, enabling non-technical business users to run queries and receive easily understandable analytical results. Gartner forecasts that by 2021, 50% of analytical queries will be generated by NLP, demonstrating its growing significance in data management.

6. Analytics & Edge Computing

According to IDC, more than 150 billion devices will be connected across the world by 2025, which will generate more than 90 zettabytes of data, creating data management challenges and opportunities. Edge Computing will enable real-time processing and analyzing data, and enhancing data management capabilities. Mckinsey estimates that out of the $500 billion IoT market in 2020, 25% requires Edge Computing.

7. Data As A Service (DaaS)

Organizations are increasingly providing access to data on an as-a-service basis, either internally to employees or commercially to generate revenue. Some companies are expected to bundle data with BI tools to provide subscription data services. In 2018, IDC forecasted that in 2020 90% of large enterprises will generate revenue from DaaS. This trend in data management enables enhanced data accessibility and monetization of data assets.

8. Data Prescription

The Future is Now! This is the ability to run simulations, where an AI recommends courses of action, after plugging in every known variable, using Neural networks, graph analysis etc. Ventana Research expects that by 2021, 2/3rds of analytical processes will involve Prescriptive Analytics.

9. Graph Databases And Analytics

Analysts are asking increasingly complex queries, combining data from multiple sources and conducting them at scale using traditional tools is a challenge. Graph databases, analytics softwares and visualization tools help in overcoming that complexity by showing how different pieces of data relate to each other. Gartner predicts that the use of graph processing will double annually for the next few years to “accelerate data preparation and enable more complex and adaptive data science.”

10. Increased Regulation

With great power comes great responsibility! The rise of data management trends has brought about increased regulation. With the GDPR(General Data Protection Regulation,2018) and other privacy Acts, data governance will be an increasingly regulated aspect of data management. Ventana Research predicts that by 2021, 1/4th of organizations will establish data governance centers to ensure compliance and mitigate risks associated with data management.

Summing Up

We are constantly breaching boundaries with technological advancements. At the core of all this, we have data. Our current systems and processes seem to have only scratched the surface of the potential of Data Management. However, necessity being the mother of invention, it’s safe to say that some of the best minds in the world are enjoying discovering creative solutions for the challenge of the century!

If you are an organization looking to manage your data and information, we at do that and more. Manage data, automate workflows, create feeds based on the topics of your choice, connect apps and see all that in a single view. Book a demo today!

Read more from

Stay updated with Needl by signing up
for our newsletter

We'll keep you in the loop with everything good going on in the modern working world.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.