Big data is the fuel that drives the many digital transformation initiatives that are underway. These initiatives lean into machine learning, which forms the building blocks for strategic programs rooted in artificial intelligence (AI). Findings from a 2021 McKinsey survey indicate that AI adoption is steadily rising, with 56 percent of respondents reporting adoption in at least one function in the business. (1)

Data comes from many sources:

    • Human-authored data (drawings, diagrams, pictures)
    • User-provided data (surveys, reviews, social posts)
    • Machine captured data (events, transactions, logs)
    • Algorithm-derived data (risk scores, fraud alerts)

Data presents itself in various forms:

    • Core data (people, places, things)
    • Transaction data (events, transactions)
    • Reference data (categories, sub-categories)
    • Metadata (characteristics, interpretations)
    • Unstructured data (objects, blobs)

The true power of data comes with the notion found in the saying, “the whole is greater than the sum of its parts.”

By combining, correlating, and creating new slices of information using the collection of data sets on hand, you can uncover opportunities to enhance customer experiences, drive efficiencies throughout business operations, and even save costs related to errors and waste. By mixing and matching data with code and algorithms, signals for when and where value might exist will begin to emerge.

Numerous aspects of identifying and assessing your data must be explored to ensure that the organization can balance the risk-vs-reward and return-on-investment equations in the initiatives they are about to embark upon. How you collect the data, store it, share it, manipulate it, and use it should be bound to the values the organization holds. Presumably, the organization’s values also align with the ethical and regulatory guidelines it must follow in the regions and sectors in which it operates.

A formally documented view will help the business, operational, and technical teams determine what processes, tools, and methods will be needed down the line.

Following the assessment to determine what exists, cataloging the data based on its source and form is essential.

Introducing into this equation the scalable multi-cloud infrastructures that open the world of data to high-powered systems, networks, storage, applications, and services, and organizations are presented with a lifetime of significant opportunities.