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Overcoming and solving the challenges of data deluge in enterprises

Henry Patishman

August 31, 2017

Overcoming and solving the challenges of data deluge in enterprises | ABBYY Blog Post

According to McKinsey Global Institute, many large companies now store more data than the U.S. Library of Congress, but processing and understanding this increasing flood of incoming data in real-time is overwhelming business executives and government agencies around the globe.

As the latest advances in technology put the value of data above all, many organizations now actively collect petabytes of data. While data capture is important, the true value is in understanding the data and using it to provide better decision-making capabilities in fast-moving environments. This makes it no surprise that capturing key data is the latest most valuable business asset, but how do we solve the challenge of understanding this ever-growing flood of data and effectively using it in the first place?

The vast amount of email, documents and other data raises the cost of operations. It increases the risk that sensitive information, such as proprietary data or customers’ personally identifiable information, may fall into the wrong hands. The data deluge also presents litigation risks and can lead to steep electronic discovery costs.

Dan Roffman, FTI Consulting,

Today, big data is ubiquitous and companies still struggle to find ways to extract valuable insights from it to make better business decisions in real-time. This lack of insight often leads to snap decisions in which a company may face extreme risk when trying to grow faster and offer new products with better services.

One-way companies are responding to the so called, “digital landfill” problem, is by introducing new roles such as Chief Data Officer (CDO), Chief Data Scientist (CDS), Data Lead and other similar positions. The key challenge facing these new data-focused specialists is to find ways for companies to make the most of the structured, semi-structured, unstructured or syndicated data sets that are currently available to them.

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The expectation is that data-driven insight will enable these executives to adopt a structured approach in decision-making that could change the way their businesses compete and operate.

Innovative approaches to data management allows organizations to:

  • analyze customer and product profitability;
  • plan a dynamic customer acquisition and retention strategy;
  • effectively measure customer satisfaction to gauge customer loyalty and retain customers;
  • segment their market and tailor their messaging for optimal results, and
  • manage overall business performance and operational processes.

While data specialists are getting more and more creative to solve their data deluge challenges, conventional wisdom suggests that they need to do more in this dynamic and fast-paced data environment.

Here are three ways to tackle these data deluge challenges head-on:

1. Discover valuable insight and intelligence from fast-accumulating data

In addition to lowering cost and implementation barriers, modern technologies help data specialists structure and sequence data to find existing or hidden patterns, enabling them to utilize the untapped insight that the data conveys. The only way to solve this approach to capturing and understanding unstructured data in real-time is to deploy software solutions that are powered by machine learning and AI, making it easier to perform big data analysis on-demand.

Finding an innovative approach to data management involves embracing all emerging technologies and data management platforms currently available in the market. These include new mobile OCR and real-time recognition technologies, mobile payment applications, web-based solutions, Cloud servers and enterprise information management systems.

2. Identify trends and correlations to drive beneficial changes

New data-mining techniques are allowing businesses to identify patterns and trends, interpret, and gain insights from vast quantities of structured and unstructured data. Data chiefs must develop powerful business analytics strategies, enabling companies to cull information from several sources while using analytics to explore concepts and correlations in thousands of variables in their databases.

Randy Bean at Harvard Business Review reports that, for the first time since he began surveying Fortune 1000 companies in 2012, almost half now say their businesses are “achieving measurable results from their big data investments.”

3. Enrich business information with data from outside sources

The explosive growth of data from outside sources, such as social media, enables businesses to proactively gather customer insights at every interaction point.  This places further pressure on data specialists to help their businesses use this information to build credibility by offering valuable information that addresses their customer needs and to improve sales, marketing and risk performance.

In addition to enriching business intelligence with data from outside sources, combining one data asset with another could generate a synergy effect that a siloed approach to data management would never achieve. Active interaction with open data portals like could possibly lead to many creative business ideas when publicly available data, is combined with an internal company data set.

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Data management has become an indispensable ingredient to successful decision making.

As more and more data accumulates, successful organizations are investing in people who can create a data-driven business culture and use innovative technologies to generate business insights.

The goal is to give people real-time access to information with context that can improve customer service, customer loyalty, and make better business decisions that ultimately increase sales.

Join us in November and learn how you can overcome the data deluge through digital transformation at our annual event in San Diego, CA, from October 25th to the 27th, 2017.

Solving Digital Transformation at #ABBYYSummit16

Digital Transformation Artificial Intelligence (AI) Mobile OCR Enterprise
Henry Patishman ABBYY

Henry Patishman

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