One of the by-products of enterprise digitization is that the business and IT have grown closer and more accustomed to collaboration. This is a good thing, particularly when it comes to enabling successful data analytics programs.
It’s essential that modern IT departments are data-savvy and ensure that the IT ecosystem can support real-time and/or near-real-time insights. In addition, IT is typically responsible for implementing processes and installing the right data platform and tools for the company’s needs.
IT Skills for the Insight-Driven Enterprise
As IT departments become more heavily involved in analytics, new requirements are emerging to ensure maximum success. For example, infrastructure skills are critical for building an architecture that can support data analytics requirements like scalability, data governance, and data security. In addition, IT teams must hone their math abilities in areas where data scientists typically excel—for example, linear algebra, statistics, calculus, and inferential geometry. Business domain expertise is another area. This generally involves collaboration with the business to determine how best to use AI and ML to address business problems, such as understanding customer journeys.
Citizen Data Scientist Movement Increasing Collaboration
As we’ve discussed previously here at the APEX of Innovation, citizen data scientists are opening up exciting new analytics opportunities throughout the enterprise. The movement is also increasing collaboration between IT and analytics teams, as it makes it easier to set corporate standards for analytics in areas such as capabilities, data access, data hygiene, data integration, and data governance. In addition, the citizen data scientist trend gives the IT department visibility into the company’s analytics platform; this involvement can be useful in determining whether the platform is the right one to deploy and also whether the data is robust enough to produce reliable insights.
Partnership Fueling the Creation of New Roles
As companies seek to strike the right balance between data capabilities and IT skills, new roles are emerging. The data engineer, for example, who helps ensure data quality and oversees the data pipelines critical to enabling successful analytics. Generally speaking, these individuals likely held prior IT positions such as systems administrator or database administrator. They typically have strong knowledge around ETL tools, varied programming languages, and database systems.
There are also changes at the executive level, for example, new priorities for chief data officers and chief analytics officers. In digital businesses that prioritize analytics, it’s becoming more common for the CIO to move into one of these roles—further emphasizing the increased alignment between IT and analytics.
For more on how these two groups will continue to collaborate in the months ahead, check out this recent TechTarget article.