By Priya Prabhu, Senior Principal – Emerging Technology, UNext Learning
Be it Kevin Spacey being roped in to lead the American version of The House Of Cards and David Fincher pulled in to direct the series, or adding the right percentage of hops in breweries to detect anomalies in enterprise networks for cybersecurity, data-driven decision-making is the backbone for all enterprise actions involving large stakes.
Statistics also reveal that companies that deploy Big Data improve their profits by 8%. Monetary benefits aside, 52% of the organisations also reveal that over 54% of them significantly improved control over their operational processes, and 52% of them understood their customers better through data. An interesting McKinsey report also shares that decisions stemming from data increase the likelihood of customer acquisition by 23% and retention by 19%.
With data analytics being inevitable today, what are some core competencies enterprises need to become data smart? What capabilities should they be looking at to make the most of untapped data? Lastly, how can such competencies be developed through training? Let’s find out
Structured Query Language
Databases house data and effective communication, retrieval, and organisation of such abundant volumes of data can be enabled through SQL. One of the most foundational aspects of data analytics, SQL empowers enterprises with meaningful insights through substantial data analysis.
Statistical Programming Languages
Excel is great, agreed. But enterprises aiming at large-scale processing of data require something more powerful. We are talking about statistical programming languages like R and Python, where codes can be written to seamlessly clean, analyse, and visualise massive volumes of data. The popularity of the Programming Languages Index also ranks Python as the most commonly used language with a market share of 28.4% and R with a market share of 4.35%. The best part is that professionals with even zero coding experience can pick up capabilities in such languages from scratch. However, we do have to note that to easily grasp these tools, one needs to have foundational knowledge on concepts in statistics such as probability and hypothesis testing, application of statistical methods to data analysis, and more.
Insights without purpose and actions are futile. Also, not everyone in an organisation comes from a technical background to infer insights from a blunt dashboard. For data and actionable to make sense for laypeople, it has to be effectively visualised. Communication backed by strong storytelling is what sells an idea or a strategy that ultimately translates into results. That’s exactly why data visualisation competencies are crucial.
Data analytics involves tons of redundant tasks and a bit of automation could help. Machine learning solves this by allowing professionals to develop algorithms to detect patterns from diverse touchpoints, find anomalies, predict outcomes, prescribe corrective measures, and more. Deploying The Right Training Enterprise Programs For Focused Competency Building If you look closely, these skills could also be standalone job roles depending on the scale of an enterprise. That’s why a vague training program for the entire IT workforce wouldn’t make sense.
What’s required is a bespoke program that identifies prevailing skill gaps in an organisation, understands goals from diverse teams, and develops a program with the most relevant and impactful outcomes. So, when you’re looking for a talent transformation partner, keep an eye out for tailored modules that would align better with your operational goals. Programs that emphasise more on practical training through case studies, assessments, platforms and tools, and labs work best for participating teams as they have firsthand experience of better performing their tasks. With outcomes directly linked back to goals, it’s vital that you join hands with the most trusted talent transformation partner for your upskilling aspirations.
Also, the decision to develop core competencies should also stem from data and that’s exactly why carrying out a skill-job gap assessment in your organisation should be the first step. Get started with that, identify niche areas and teams that require training, and deploy the right training program. RoI would find your way automatically.