Forrester revealed in their staggering study that close to 73% of data in an enterprise goes unused for analytics.
I am pretty sure data also sits in silos at your organization. In a complex swamp. It’s gathering digital dust. It’s filled with manual errors. That data is already a liability.
Plus,
- That data is an invisible tax on your balance sheet
- The smart data analysts in your company are puzzled with inaccurate data insights
- Sifting through this data complication is killing productivity
So how to overcome this operational data drag?
That’s when ‘AI in data management’ comes in.
But before we look at some data management and AI features that could benefit data efficiency, let’s analyze the problems better.
The pain points that AI data management solves
Data management pain points faced by data professionals.
Data efficiency = Most value obtained from your data.
This involves the least amount of effort and resources.
For a data professional like you, this is a constant battle.
Here are a few data efficiency problems you face.
The what and which of data
Data cleansing problems faced by data professionals.
The first pain point is significant.
Your data is inaccurate, incomplete, and inconsistent.
Probably even outdated.
Your data team is spending enormous time on,
- Data cleansing – Identifying and fixing errors, typos, and formatting issues manually.
- De-duplication – Finding first, then merging multiple data records for the same entity.
- Missing values – How to handle this incomplete data? Filling it in, ignoring, or just dropping it?
Data quality that’s poor erodes trust in that data. Incorrect insights lead to flawed business decisions.
AI data management solves the above pain point with,
Automated data quality
Automated data quality benefit of AI in data management.
With our platform, data management with AI is data cleansing on steroids. Instead of a manual cleanup, AI agents detect and correct anomalies.
To solve de-duplication, data management for AI uses semantic matching to identify similar data records. For missing values, it’s predictive imputation.
This estimates and fills gaps based on correlations with data. DataManagement.AI simply asks you to specify what data you seek. The rest is automated to perfection.
This is a far cry from other AI management tools that ask you to either manually upload a spreadsheet or make you clean the data first.
Data silos and fragmentation
Lack of visibility and manual process problems faced by data professionals. Data is rarely stored in a singular place. It’s scattered across department folders, outdated systems, and formats.
This could be cloud, spreadsheets, or an ERP.
These silos are difficult to access and leads to,
- Single source of truth – Confusion and inconsistency galore. There exists different versions of the same data.
- Manual processes – Your data team is spending countless hours pulling, cleaning data from varied sources.
- Lack of visibility – There is a lack of a holistic view without an unified dataset.
Data management for AI solves the above pain point with,
Automated data unification
Automated data unification benefit of AI in data management.
Generative AI in data management, which DataManagement.AI empowers you with, eliminates manual processes.
As seen in the image, our data management tool automatically discovers and extracts data from a wide variety of sources.
Our AI-powered tool intelligently maps relationships. This is between datasets or between systems. This is how AI and data management combine to build a unified and cohesive dataset.
Be like the Panda here in our social media post and get your data sorted in a click.
Data volume and complexity
Scalability issues and decreased performance problems faced by data professionals.
According to DemandSage, by the end of 2025, the world will generate 181 zettabytes of data.
That’s a massive increase from the 120 zettabytes generated in 2023.
This staggering statistic leads to a variety of data challenges to your data team, such as,
- Issues in scalability – Your legacy systems are struggling to process, store or analyze massive datasets quickly.
- Decreased performance – Building models or running queries on large volumes of data is slow, leading to delayed insights.
- Diverse data handling – Whether structured (databases), semi-structured (JSON) or unstructured (text, images, video) data, a consolidated data handling tool is the need of the hour.
We solve the above pain point with,
Dynamic stability
Dynamic stability is a benefit of AI in data management.
Our data management artificial intelligence system can dynamically scale massive data volumes.
No reliance on rigid legacy systems. DataManagement.AI automatically adjusts computing resources.
Assume a scenario where a large dataset needs processing.
Our data management generative AI can provision more resources to speed up tasks. You get optimized performance with massive cost-efficiency.
No more diverse data handling. Thanks to our AI-powered tool, your AI data management systems can work with all forms of data. Structured, semi-structured or unstructured – you name it.
No need for your data teams to use numerous other tools suited for a particular data type. Let’s see how your data looks on an AI data management tool. Sign up for a free demo.
Data lineage and governance
Data lineage and compliance risks are problems faced by data professionals.
Data gets chaotic. That’s if clear rules or documentation are not in place. Some non-AI data management risks include,
- Data lineage that’s unknown – Where is the data coming from? What transformations did it go through? or Is the data trustworthy? Not having answers to these makes auditing a nightmare.
- Lack of ownership – If no one owns the data, there is no one to be held responsible towards its quality or accuracy.
- Compliance risks – The lack of proper governance makes it harder for data to be regulated under GDPR or CCPA. This could lead to hefty fines and reputational damage.
Generative AI for data management solves the above pain point with,
Automated end-to-end data lineage
Automated end to end data lineage is a benefit of AI in data management.
AI for data management works by automatically tracking down data. The image above shows DataManagement.AI into action.
Instead of manual documentation, our AI agents log every transformation, merge or data change. You now have a detailed audit trail. This happens from source to destination.
Accessibility and literacy gaps
Data accessibility and lack of context are problems faced by data professionals.
Data is a powerful asset. But do data professionals really understand it?
The following issues prevent the building of a consolidated data report.
- Barriers to entry – Your business or organization relies on data reports for insights. A lack of technical skills or access to the right tools can hinder this. You then find bottlenecks that slow down decision-making.
- Lack of context – No proper metadata or documentation leads to data misinterpretation.
AI in data management solves the above pain point with,
Visual interfaces
Visual interfaces are a benefit of AI in data management.
Data management for AI systems, such as the one from DataManagement.AI comes with drag-and-drop visual canvases. A singular flow diagram that maps your entire data workflow.
Our Data management artificial intelligence handles both data transformation and integration aspects.
This also delivers on the data democratization aspect.
Even a non-technical personnel from your data team can understand how to use the data in a compliant manner.
Plus, our AI-powered data management platform generates a metadata catalog.
This provides context. It answers your questions such as, “What does this column, in this particular table mean?”.
This makes your data team understand where the data comes from.
Data management and AI services by DataManagement.AI
AI in data management benefits to businesses.
DataManagement.AI powers your data management with intelligent AI agents. To handle vast amounts of overwhelming and complex datasets, we have built a breakthrough solution – Chain-of-Data.
The image above shows you our proprietary Chain-of-Data solution at work.
You can seamlessly link every step of your data journey into a singular and efficient data matrix.
Your operations run smoother, with better insights, and help you save more.
The key advantages of our data management and AI services are,
Data pipeline on-the-go
Currently, data analysis requires time spent in extracting, transforming, and loading (ETL). This goes into separate data warehouses. Our data management and AI services eliminate all that.
You can directly query and analyze data in its source system itself.
No need for extraction, prep time or delays. Let your data teams work on other tasks as your data systems run on autopilot.
This approach bypasses the need for a complex data pipeline with tedious data preparation. This enables you immediate access to information without delays.
In-place data interaction
Numerous other data solutions will make you move your data. Your data now has numerous copies which leads you to lose control. DataManagement.AI’s data management and AI services solve this issue differently.
Our AI-powered platform lets you work on your data exactly where it is. No replication. No extra storage.
Only secure and direct access with full sovereignty. It’s just you and your beloved data locked-in for a beautiful honeymoon.
The honeymoon doesn’t end there. A simplified data architecture also reduces cost. Your data never leaves its original location.
You do with risks and complexities of data movement. You now have peace to sip in your coffee with full ownership throughout the data lifecycle.
Your model for any system
Time to own your roadmap. Gone are the days when you had to submit to another vendor for data and its governance.
Keep control of your data. Your data model should fit across any cloud, making it future-proof.
Our data management and AI services let you take full control of your AI strategy.
You get the flexibility of choosing your preferred model across any cloud environment.
It’s your own ‘composable architecture’. You can integrate new technologies and services, whenever they emerge. Your control means your governance policies and model choices.
We empower you to build your customizable and adaptable AI roadmap that evolves when your business needs it.
Your AI without limits
Forget ripping and replacing your AI. Seamlessly integrate AI into your existing operations. With our data management and AI services you can plug in pre-built and industry specific workflows.
This ensures instant impact over HR, sales, CX and more.
Our AI-powered platform offers a library of pre-build AI agents. These are plugged directly into your current systems. With this, there is no major overhaul of your tech stack.
You achieve instant impact across critical business functions. You accelerate your AI adoption journey without the typical friction you face now.
Always-on security
DataManagement.AI’s data management and AI services lets you innovate freely. That’s because every data request is secured with granular access policies.
No way can anybody push the ‘Delete’ button to lose or edit data manually. You decide…precisely who accesses ‘what data’ and under ‘what conditions’.
Thanks to continuous authentication, you verify user identity throughout a session. Our built-in compliance features help you meet regulatory requirements.
With a multi-layered and robust data framework, you focus on developing new products without worrying about data breaches.
AI Data Management – Your AI compass
What is the future of data management?
Throwing more resources?
Nope. It’s the fundamental shift that you take to approach data.
Do you still feel confident about reactive, manual efforts in your data systems?
Time to switch from reactive to productive.
We can show you how.
Our customers are seeing tangible results.
- 60% increase in efficiency
- 20x productivity gain
- 50% in cost savings
Leverage AI in data management to automate, optimize, and streamline your data processes.
Let us show you how!
Schedule a demo today and start building your intelligent, efficient data ecosystem.
