Your Content Repository Could Be a Data Gold Mine for IDP

#capture #idp #ocr #ecm

Takeaways

Dark data is data that can't be analyzed — and it's everywhere.
Approximately 55% of enterprise data is dark.
47% of dark data could already be living in content services or ECM, waiting for extraction.
Intelligent Document Processing rapidly makes sense of dark, unstructured data, preparing it with the structure needed for analysis in a data lake.

Organizations collect huge volumes of information, but very seldom, if ever, analyze all of it. Unanalyzed “dark data” is hidden everywhere, from PDFs and spreadsheets to Teams chats and nearly every place where humans exchange ideas.

With it commonly accepted that anywhere from 80-90% of enterprise data is unstructured¹, and almost half of enterprise data goes unused in decision-making², there are some insanely valuable insights locked away.

In his adventure of the Copper Beeches, Sherlock Holmes exclaimed,

"Data! Data! Data! I cannot make bricks without clay!"

Data is paramount to informed decisions, and even Mr. Holmes — a man capable of making the most astute, albeit absurd, deductions — needs data to succeed. Your organization is no different.

But while the amount of dark data can be alarming when put in terms like zettabytes or compared to lost floppy disks, 47% of it could already be in an ECM or content services system³.

Those are our proverbial mineshafts. That’s where the gold is.

It’s time to go spelunking.

What is Dark Data?

Dark data is any data, structured or unstructured, that is collected but not utilized to inform business decisions.

While structured data stored in legacy systems, personal devices, private spreadsheets, and department chats can contribute to dark data buildup, unstructured document/content data wins as the biggest offender of data gone dark — and it’s not even close.

How Does Unstructured Data Go Dark?

Unstructured data can go "dark" when it gets lost in the shuffle of:

Data siloes
Legacy systems
Poor lifecycle management
Bad document storage practices

Even properly stored data can become dark if it's too complex to parse into data lakes for analysis, or is directly loaded into a lake in its raw format.

The reason unstructured data is so difficult to master is primarily because it is often human-generated — arriving in many differing document and content types, including emails, paper files, social posts, images, or any document without a consistent format or layout.

Some Unstructured Data Statistics (and Absurd Holmesian Deductions)

Today, about 175 ZB of data is created, replicated, and consumed each year — expecting exponential growth.⁴ That's about 122 quadrillion floppy disks in case you were wondering...
Based on IDC's global datasphere predictions, yearly world data will reach almost 400 ZB by 2028.⁵ That's more than double the data... and floppy disks.
Of the 393 ZB of world data in 2028, 81% will be generated by enterprises hunting for data analysis and gen AI.⁵ That's 318 ZB of data.
Taking the commonly cited statistic that 80–90% of the world's enterprise data is unstructured⁶ and being conservative, by 2028 enterprises alone will generate more unstructured data than the world of today.
Current reports assess that 55% of enterprise data is unanalyzable, or "dark."⁷ So by 2028, you'd be better off taking 122 quadrillion floppy disks containing important enterprise data and recycling them for plasticware at the office.
Of the unstructured enterprise data out there, nearly half is exchanged via a central content repository like an ECM or content services platform.⁶

How Can I Better Utilize My Content Data?

Start by understanding where unstructured data lives. Because dark data has almost a 50% chance of being unstructured data contained in a centralized content repository, that’s a great and easy place to start.

Unstructured content flows into your organization through many ingestion points within inbound communication channels like:

Email or chat
Uploads and sharing
APIs and integrations
Automated systems

Ideally, the end of that workflow lands the content in some form of centralized system.

So that’s where the gold is.

Use AI Better — Find Your Data Gold

Intelligent Document Processing (IDP) combines natural language processing, machine learning, and a variety of capture methods to organize unstructured data. It can rapidly capture, label, index, and route data as it comes into your organization — or, unlock that 50% of dark content data sitting in your repository for analysis.

How Does IDP Enable Data Analysis from Unstructured Data?

Unstructured data is hard to parse automatically and slow to process via scripts — because humans think in words and context clues that become riddles to Python.

Humans also create many variations in how content is organized, which is not ideal for extraction.

The way IDP analyzes documents — focusing on context, natural language patterns, and learning over time — allows it to:

Translate content to a finer semantic layer
Provide necessary structure for data analysis
Shine light on dark data for extraction and analysis

Your content repository is a mine. Data is gold. IDP is a shovel.

If Holmes were here, he’d be stacking gold bricks — because data, data, data!

The post Your Content Repository Is a Data Gold Mine — Here’s How IDP Can Mine It appeared first on keymarkinc.com.