The Big Data Conundrum and Opportunities

The Big Data Conundrum and Opportunities

Emerging technologies like machine learning and artificial intelligence hold the promise of helping companies to turn today’s challenges into tomorrow’s opportunities. One of the biggest challenges that companies faced today is how to manage the explosion of data that flow into and out of their organizations—mostly in the form of unstructured content like documents and emails that aren’t easily managed by ERP and other systems designed to manage structured data.

The problem of how to manage an ever-expanding universe of data is a bigger problem than you might imagine—one that goes beyond storage and security to simply figuring out how to digest it all and turn it into meaningful, actionable information.

A big, big problem

Until 2003, humankind generated a TOTAL of five exabytes of data—equal to one billion gigabytes. That is the equivalent of ALL the words EVER spoken by any human being (stored as a txt file).

Today, we produce five exabytes of data every TWO days.

Where is all of this data coming from?

The majority of it is it is unstructured content—audio and video files, Word documents, PDFs, presentations and images that cannot be efficiently managed using structured data systems like enterprise resource management systems.

Here are just a few examples:

  • Facebook Messenger users share 216,302 photos.
  • Twitter users send 9,678 emoji-filled tweets.
  • Instagram users like 2,430,555 posts.
  • YouTube users share 400 hours of new video content.
  • Snapchat users watch 6,944,444 videos.
  • 3,567,850 text messages are sent in the U.S.
  • Siri answers 99,206 requests.

Creating an even bigger opportunity

Big data companies specialize in transforming their client’s data into knowledge that can better inform their business decisions and streamline their business processes. But before companies can mine their data for business intelligence or leverage it to inform machine learning-driven automation, they need to transform everything into digital content in a way that extracts meaningful data from a bunch of noise.

For most companies, including middle market organizations today, one of the first challenges to arriving at the promised land of big data is extracting information from unstructured content—without human intervention.

That’s where intelligent extraction and digital transformation solutions, designed to identify actionable data from unstructured content like invoices, sales orders, bills of lading and just about anything else you can think of, come into play.

Digital Transformation to the Rescue

Digital Transformation Platforms, like Artsyl’s docAlpha, integrate with existing back end business systems to transform the unstructured data in documents stored in ECM systems into structured data that can be stored and managed in ERP systems—automatically, with minimal human intervention. For many organizations, the low-hanging fruit for intelligently capturing data from unstructured documents are routine back office processes like accounts payable and sales order processing.

For accounts payable staff members, applying intelligent capture translates into the elimination of routine tasks like invoice/order matching, manual approval routing and G/L coding, transaction data entry and document filing. For executives, it means that data and documents are transformed into information instantly, resulting in greater visibility to critical business KPIs, including cash flow. For customers, this can translate into greater responsiveness and better service at a lower cost.

Once organizations embrace intelligent capture and automate data- and document-dependent processes like AP or sales order processing, they are able to apply the same approach throughout their organization, achieving greater efficiency and visibility for ALL of their critical business processes.

To explore how Digital Transformation and Big Data can help automate and accelerate operations for your organization, contact your Artsyl Technologies representative.


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