Ungated

Investing in digital transformation technologies can be a waste of money if your company forgets one important point. That point is, no matter how cutting edge the tech or tool may be, people are needed with specific technical expertise in order to derive true business value from these investments.

Unlike large enterprises, mid-market companies often try to find this expertise in their IT manager, hoping a jack-of-all-trades approach will take care of it. This is an unfortunate mistake, since it would require the IT manager to have unusual command over a long laundry list of duties, from data integration, ingestion, and preparation to data security, regulatory compliance, data science, and building pipelines of data ready for executive reporting from multiple cloud and on-premises environments. This is not just a tall order for a mid-market IT manager to pull off, but likely an impossible one.

A chief data officer (CDO) is focused on—you got it—data. Most mid-market companies understandably don’t have a CDO, which means they don’t have anyone who assures regulatory compliance for data handling while managing and exploiting information assets, reducing uncertainty and risk, and applying data and analytics to drive cost optimization and revenue objectives. For IT managers to fulfill a CDO role, they’d have to be equipped to bring a global perspective to company data, help their organization gain competitive advantage over peers, and manage data and analytics. They’d also need the ability to secure data, transform it into valuable business information, lead digital transformation initiatives, and use data for growth and operational efficiency.

The primary job of a cloud engineer is to keep cloud data centers operational and secure for ecosystem users to be able to store and access their data. Cloud engineers are experts in minimizing downtime, managing access to data, managing compute and storage, and setting up cloud architectures for clients, tenants, and containers. They also monitor data center hardware, servers, networks, and communications systems for operational continuity and efficiency.

Mid-market firms also need a way to channel the talents of a data security expert, CISO, or cybersecurity director to ensure cyber-security for the company’s data. Data security experts must keep current on emerging threats while executing data security strategies to fend off and remediate attacks. This involves a wide range of duties, including working closely with the IT team to run the company’s Security Operations Center (SOC), constantly monitoring servers, networks, and workstations for security threats, and staying up to date on the changing compliance laws and regulations for the business, to name a few.  While larger IT teams have bandwidth to fill cybersecurity needs inhouse, many midmarket IT teams do not have capacity for the 24/7/365 monitoring and security edits needed to thwart attacks, let alone bandwidth for executing on mitigation and response strategies needed to overcome them.

A data engineer’s primary job is to prepare data for analysis or operational uses, which involves integrating data from different sources, as well as implementing and executing data profiling, cleansing, transforming, and normalizing data. Data engineers also work with data in motion and use master data management to ensure data consistency across an organization. Finally, a data engineer is your go-to technical resource for database construction and management, helping to optimize the company’s data ecosystem.

It should be clear now why a mid-market IT manager should not be expected to take on these additional professional roles, but in case there’s any doubt, keep in mind that a data scientist is also needed. Data scientists develop algorithms and leverage deep learning models to analyze data with artificial intelligence and machine learning. The data scientist creates the “brain” of the data analytics solution to position it for providing accurate answers based on business information. Data scientists also mine data to find opportunities for business growth and efficiency. Ideally, the data scientist uses tools that enable non-technical business users to query data sets without having to write SQL or other code.