Navigating the Sea of Data in the Digital Age

Every business is looking for a viable way to jumpstart their operational digital transformation to become more competitive and customer-centric, which requires agile and scalable processes. The key is in harnessing big data to unlock the hidden insights of digital customers, channels, markets and business processes. For example, data-driven insights improve personalization and contextual marketing opportunities that can transform user experience (UX) and increase market share.

UX is a major catalyst for digital business transformation because it eases customers interaction with products, brands, and companies. The multichannel approaches powered by the web, mobile, social media, cloud, IoT, and other touch points delivers data that fuels opportunities for delivering better UX and market growth. This can be seen in a recent Dun & Bradstreet study showing 58 percent of marketing executives using data to find new customers, and 55 percent using analytics to grow lead generation. Despite this reality, harnessing huge amounts of data to drive digital transformation is easier said than done.

The Big Data Dilemma

A recent Computer Weekly article discusses how the challenge of digital transformation is very real for CIOs and CEOs. Speaking at the Gartner ITxpo in Barcelona, Gartner executives discussed their recent study citing concerns of slow digital transformations that lead to competitive disadvantages by two-thirds of business leaders. While there are several challenges that lead to these concerns, many of them flow from the huge amounts of data and how to deal with it.

There is a single primary challenge to digital transformation through data: while digital transformation organically creates new data, it’s a much more complex process for data to create digital transformation. This can be seen in two hurdles businesses must overcome to leverage data from digital transformation:

  • Petabytes of data flowing in from many sources
  • The difficulty in storing, aggregating and analyzing data

Today’s data can be structured (transactional) or unstructured, publicly available or privately collected, and its value comes from the ability to store, aggregate, and analyze all of it, quickly. The opportunities to leverage new data for valuable insights and competitive advantage are endless. The sticking point is that organizations will face many challenges stemming from the influx and analysis of a sea of data.

Better Data Access

With the new emphasis on agility through digital transformation, business leaders have to embrace a business culture where they see how data comes from all sources and departments while finding a way for everyone to properly access it. The democratization of gathering, storing and accessing data requires eliminating data silos to include the multitude of cloud, social, IoT, smartphone, kiosk and other external applications or unstructured data sources that generate massive volumes of information.

Businesses must develop a strategy and process for moving the data into a state where it can be accessed and manipulated by broadly accessible tools that can be intuitively used by the entire workforce across departments. This end state can come from the use of a variety of easy-to-use, self-service AI-powered applications and tools that provide data manipulation and analysis expertise to business users.

There are ways to not only extract insights from the raw data, but also to speed up this process, giving the organization faster and more efficient access to actionable data. This leads to another challenge of first storing and aggregating all of that data in a unified way.

Sifting and Saving Data

Business users will need a way to sift through and extract the important information hidden within massive quantities of data. One key way to achieve this goal is with an aggregation and storage partner that can apply a single toolset that synchronizes the data curation process so that it can be fed into analytics and BI tools for actionable outcomes. Hidden within this process is another challenge of ensuring that the data clean and accurate.

Once again, the right partner can support methods of data trail verification and accuracy via development of a centralized data lake for auditing governance and access. By developing a unified repository and access point, businesses can implement data visualization and analytics tools that can inform other applications and platforms that can deliver actionable data. The combination of big data and machine learning tools can put qualified, clean, reliable data into the hands of more employees for them to then analyze and make fast, informed decisions. This is the foundation of building a digital transformation pipeline that can make businesses competitive, agile, responsive and innovative in the digital age.


The strong interlock between digital transformation and big data is driving change to traditional business models. Businesses need to create a foundational roadmap that:

  • Provides a unified way to store and aggregate huge amounts of data from countless sources
  • Ensures data integrity
  • Provides self-service tools and data access for all employees
  • Incorporates a flexible, open platform that can easily integrate with future technologies
  • Making sure enterprise data is clean, accurate, and easy to find, analyze and share

In the end, the goal is not only company adoption of big data and analytics in business processes, but acceptance of big data and analytics as a way of doing business. With visibility into all parts of a modern business, CIOs, and CDOs can unify business leaders and IT under a clear data roadmap, and be the catalyst for data-driven organizational changes that will help their companies remain competitive. With the support of the right digital transformation partner, businesses can navigate the sea of data in the digital age to achieving their digital transformation goals. This partner can help to create a process for a holistic data pipeline that can constantly store and aggregate that continually growing body of data from countless sources. This sets the stage for ensuring data integrity, self-service access and analysis applications that can be accessed by everyone across the business. The result is a digital transformation platform that gives CIOs and businesses a foundation for brand, market and bottom-line growth.

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