The global data analytics market has witnessed strong, continuous growth in the past few years and is projected to continue this same path.
A recent market study shows that the data analytics market is expected to grow 30% from 2020 to 2023. With the help of data analytics, organizations can now leverage data to extract valuable insights, which are used to create actionable decisions. Read on to get a glimpse of functions in this industry and what skill-sets are required to enter this massive and increasing market.
Organizations use analytical solutions that empower them to better target consumers, continue vendor consolidation, and increase access to cloud-based models, enterprise-grade security, and data governance solutions offered by market vendors.
The rapid expansion of data generated by IoT devices has uncovered an entirely new field of study for analysts. While web or app patterns are already enjoying the full attention of analysts, there are amazing opportunities in profiling patterns, behaviors, and understanding data from these new sources.
While it is true that data is at the heart of any digital business today, data alone cannot provide all the answers. Companies require insights and actionable paths they can take to optimize and adjust for maximum results.
Due to the complete digitization of all the products, managers, executives and entrepreneurs around the world have digital transformation at the top of their agenda. Nowadays, it’s almost impossible to imagine how the businesses of the future will look like without mentioning the transformation of their business to digital.
Machine learning and AI help businesses jump light years as the technology improves automatically through use or experience. Besides constantly redefining our experience with products across all ecosystems, they became the Holy Grail for many companies, marketers, analysts, and programmers around the world.
You are an expert in programming and all the intricacies of the software. You could become the go-to person for any programming-related queries and software troubleshooting for reporting activities. In addition, you would carry out other analytics like predictive or prescriptive modeling in order to have data-driven decision making.
More often than not, the best programmers are not the best modelers and vice versa. That is perhaps, because you need different kinds of temperaments for these two different skill sets. The person who creates the model is technically creating a statistical model in order to test a hypothesis of a business problem and come up with a solution that is a derivative of the data.
You can conceptualize and create analytics solutions to help solve business problems. You understand the problem to be solved and have the expertise to create the most appropriate analytical framework to solve the problem. You also recommend the best method or sets of methodologies to be used to solve the problems. You are the analytics architect.
You are able to create the most practical, impactful story that helps clients change their businesses. You have the ability to understand the business of the client, their pain points and pull together insights from the analysis to weave together powerful strategies for the client.
Your job is to convince prospective clients to use analytics in their business and show them how they can benefit. Potentially, you are convincing managers and owners to purchase analytical tools.
Summarizes raw data and converts it into a form that can be easily understood. Describes in detail an event that has occurred in the past and derives patterns from past events or draws interpretations to better frame future strategies.
These analytical tools aid an analyst in digging deeper into an issue to arrive at the source of a problem. In a structured business environment, tools for both descriptive and diagnostic analytics go hand-in-hand.
Any business pursuing success should have foresight. Predictive analytics helps businesses to forecast trends based on the current events. Whether it’s predicting the probability of an event happening in future or estimating the accurate time it will happen can all be determined with the help of predictive analytical models.
This type of analytics explains the step-by-step process in a situation. For instance, a prescriptive analysis is what comes into play when your Uber driver gets the easier route from Gmaps. The best route was chosen by considering the distance of every available route from your pick-up route to the destination and the traffic constraints on each road.
Below is a list of top 10 industries applying big data and analytics, according to Research Reports World.
Review this article from Forbes about how to start a career in analytics.
In addition to your School of Management courses in analytics and management science and systems, you may consider building your skills in SQL, Python, Excel and statistics with some of these resources.