The Increasingly Data-Driven World

Companies successfully charting a course to a data-driven future are retooling business strategies, adopting new technologies, and onboarding data experts.

Whether the industry is finance, health care, or manufacturing, organizations are facing a veritable data tsunami. Experts say approximately 2.5 quintillion bytes of data are created each day with over 90% of this global bounty generated in the last two years.

There’s little question the data deluge holds the keys to transforming business practices and unlocking new revenue opportunities. A survey of 2,300 global business and IT leaders by MIT Technology Review Insights, in association with Pure Storage, found 87% of respondents emphasizing the importance of data for delivering better results for customers or clients and for driving business growth (87%). Eighty-six percent of those surveyed said data is the foundation for making important business decisions.

At the same time, it’s an on-going struggle to figure out exactly what data is critical to the corporate mission — let alone what experts and technologies are required to effectively manage and analyze data to create competitive advantage.

In this week’s #IDGTechTalk, we set out to explore the impact of increasing data volumes on the business as well as what CIOs should do to prepare their organizations for the incoming onslaught. Read on for the highlights of the conversation:

Rising data volumes have widespread impact.

There’s been dramatic growth in data driven by cloud and mobility, especially as it relates to improving reporting and security. Industries such as healthcare and life sciences are among the biggest drivers of the data explosion. There, big data reserves are being fueled by patient records, product research, scientific testing, analytics, disease surveillance — all of which will continue at a rapid pace in light of the aging baby boomer population.

While more data has value, companies often miss out on the benefits because they fail to properly align data and analytics to generate useful insights. To this point, companies often don’t do what it takes to ask good questions of the data and wind up on a fishing expedition instead of targeted hunt.

There isn’t a single data source that’s considered the gold standard.

Customer data, Internet of Things (IoT) data, even data residing in decades-old structured databases has value and is considered fair game in the quest for data-driven transformation. There appears to be a debate among the data management crowd as to what’s more important to an organization — structured data or the new world of big data. Most experts advise CIOs and IT organizations to ignore the noise and pick the best tool for the job depending on the need.

To take that argument further, it’s no longer a question of whether data is valuable or not valuable, but rather how an organization can practically leverage the resulting analysis of that data. All the machine learning and AI in the world is useless if the insights can’t be applied to advance core business objectives. In the end, what’s essential is to understand the business objectives and define the right data mix to achieve those goals.

Storage, analytics, and data-savvy personnel need to be shifted into high gear.

More data means more opportunity for insights, which means IT organizations need to staff up with the right data science expertise (think skill sets like Hadoop and Kafka). To ensure data becomes an asset, organizations have to foster more engagement and skills sharing between IT and business units. At the same time, increasing volumes reinforce the need for robust data quality, data governance, and data classification practices.

Storage also becomes a greater consideration. Enterprise storage requirement are increasing by 30% year-over-year as businesses struggle to define proper lifecycle management of the data they hold. The balance is being able to handle increased volumes while being more selective about what specific data is stored and managed over time.

Lack of data science talent remains a challenge.

One of the biggest hurdles to promoting the data-driven enterprise is the lack of available talent, including data scientists and experts in artificial intelligence (AI) and machine learning (ML). CIOs need to work with their HR organizations to retool hiring and retention practices to attract highly skilled workers and do what it takes to keep them.

Some businesses, overwhelmed by the data deluge, will try to do too much without a clear understanding of their objectives or critical business goals.

New tools and processes that democratize data are central to moving forward.

New tools that can help uncover dark data, locate sensitive data, and transform unstructured data into searchable standardized content are critical to fostering a data-driven enterprise. There’s also a need to democratize data via self-service analytics so it becomes a true organizational asset, not just the domain of highly specialized data experts.

Perhaps most important is for businesses to slow down and craft a strategy that clarifies what data is useful and how it’s going to be used. CIOs need to take the lead influencing leadership on what needs to change organizationally to create and nurture a data-driven culture.

How has data made a difference in your organization? Feel free to weigh in in the comment section below. And as always, please join us every Thursday at 12pm ET for the #IDGTECHtalk.

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