Xoobies founder MQ Qureshi spearheaded a roundtable discussion on the current and future use of big data at the 2018 Leadership in Big Data & Analytics Forum in Chicago on December 4. The roundtable discussion, “Using Big Data for the Future,” focused on several big data-related topics, including:
Big data is rapidly evolving, and organizations are constantly on the lookout for ways to quickly and seamlessly capture and analyze structured and unstructured information. As such, organizations are regularly deploying state-of-the-art data collection and analysis tools.
However, organizations must understand exactly how they can use big data to drive meaningful results. If organizations establish big data strategies and goals, they can map out their technology investments accordingly. As a result, organizations can determine how to use machine learning, artificial intelligence (AI) and various data collection and analysis technologies to gain the insights they need to succeed both now and in the future.
Eliminating the guesswork surrounding big data is key. If an organization understands the value of big data, it can find ways to retrieve information from myriad sources and analyze this information properly. This organization also can leverage big data technologies across its workforce – something that could help the organization gain unprecedented insights day after day.
“As we start thinking about the things that are going to shape the future of big data, there are so many buzzwords out there,” Qureshi pointed out. “Everybody talks about machine learning … and machine learning and AI can be demystified to solve a very specific set of problems.”
2. Data Privacy
Organizations have immediate access to data, but they must manage this information carefully. Because if an organization fails to secure sensitive consumer information, it risks data breaches, along with associated customer turnover, brand reputation damage, revenue loss and compliance violations.
Data privacy is a top concern for consumers globally. Furthermore, the General Data Protection Regulation (GDPR) and other data security mandates are now in place to safeguard consumer data.
Meanwhile, organizations are tasked with finding the right balance between data privacy and convenience. If organizations understand the challenges associated with securing consumer data, they can take the necessary steps to protect this information against myriad threats. At the same time, organizations can implement technologies to ensure that they can provide convenient systems and processes that won’t put consumer data at risk.
“Privacy is an issue and is something that we care about, but it’s also being balanced with the fact that a lot of our privacy is sacrificed in the name of convenience,” Qureshi stated.
3. Chief Data Officer
In the past, organizations employed chief digital officers (CDOs) to manage all aspects of their respective digital operations. But CDOs sometimes failed to help organizations achieve their respective digital aspirations.
Organizations today may be more prone to employ a chief data officer over a chief digital officer. With a chief data officer in place, an organization can employ a talented data expert who can help it get the most out of the information at its disposal. Additionally, a chief data officer may allow an organization to explore ways to optimize its data collection and analysis technology investments.
“The CDO used to be known as the chief digital officer, and we’ve started seeing that role come down a bit in terms of prominence,” Qureshi indicated. “The chief data officer has the opportunity to bridge the gap between business and technology and bring those things together to form a big vision.”
4. Talent Management
There is no shortage of talent available to organizations that want to add to their data analysis teams. Conversely, data scientists and other data experts are in high demand, and organizations must do whatever it takes to attract and retain talented professionals who possess in-depth data analysis skills.
Organizations should dedicate time and resources to find data experts. They also must try to cultivate data analysis skills within their existing workforces.
If an organization offers big data training programs to its employees, for example, it could empower its workers with valuable data analysis skills. These employees will understand how to analyze data and generate actionable insights from it. Perhaps best of all, workers who possess data analysis skills may be better equipped than ever before to retrieve meaningful insights that they can use to help their respective organizations grow.
“It’s not necessarily that we don’t have a lot of talented people around, it’s maybe that we, as leaders, aren’t creating an environment that is making it [the field of] data science available to people who may want to be a part of it,” Qureshi noted.