As businesses have become more technologically dependent, IT departments have been tasked with a wider range of duties and responsibilities. Often, these professionals are responsible for managing internal systems and supporting the business directly, managing cloud-based solutions and externally acquired data, and managing the security risks that come from an ever-growing range of systems. As big data becomes a larger part of the landscape, tech departments are being squeezed, creating a bottleneck that affects the majority of a company’s operations.

Expectations regarding the function of IT personnel have grown significantly, and big data has introduced a new paradigm to which is notably difficult to adapt. Before large-scale data analytics became a new norm, data was often siloed based on origin or function, and analytical functions were specialized based on the inherent systems. Now, the volume and variety of data has increased, and companies want to be able to leverage all of it to draw conclusions even if the current physical barriers create a notable challenge.

IT environments can involve thousands of servers, when both in-house and cloud options are examined, with even more containers separating information. As data users begin to have expectations regarding how business intelligence systems should respond, IT professionals are tasked with locating problems across ever growing systems, many of which feature different technical frameworks and far-reaching connections outside of the physical purview of the business.

How to Prepare for Tomorrow’s Demands

To ensure that IT departments are prepared for the changes that big data has spawned, a new approach to data management is required. Tech teams, and businesses as a whole, must learn to exercise greater control over their data centers and institute the technological solutions that are designed to manage these shifting demands. A move away from siloed environments will be a necessity to make information accessible across the board while multi-datacenter support must be available to ensure the continuation of operations.

Businesses need to be open to innovation. Improved real-time anomaly detection will become critical to spot issues before they produce problems while stream processing needs to be implemented for increased performance of custom analytics. The institution of direct programmatic access using tools like SAS and R will also be valuable for data maintenance.

It also means companies need to hire the right the right IT professionals with the necessary skill sets to manage the tasks. Without a strong tech team to drive change, many organizations will find themselves battling legacy systems and old ways of doing business. If you are looking for skilled big data professionals to join your team, ITStaff can help you find the right candidates. Contact us today.

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