Knowledge Series – Hottest skills for Analytics in 2018December 22, 2017
As companies try to match up and adapt to the modern workforce, they are not leaving any measures aside to attract the top tech talent. Data analytics and statistics have become a routine line of work in almost all industries, and along with it comes the various programming languages and tools to make the data analytics intervention and integration more effective.
To better understand what companies are looking for in terms of skills in technology, various surveys are conducted, basis the job requirements on the recruitment portals, specifically for the IT sector. The conclusion is, that these are indeed very exciting times, because on one end we see a rise in machines which in turn increases productivity, and on the other we see automation and efforts towards it increase tremendously. We are seeing the onset of the driverless car, to delivery drones, which are changing the way the analytics industry works. Therefore, it becomes essential at such times to continuously up skill ourselves to be lucrative in the job market.
Since a while now Big Data has been quite the buzzword in the industry, while it still continues to stay popular, there is a growing interest in Machine learning, predicted in the coming year. Especially since companies are moving towards consolidating and democratising Artificial Intelligence, and a huge part responsible for achieving that is Machine Learning.
In the year 2018, the combined knowledge and expertise in Big Data along with Machine Learning ensure the opportunity of you securing a job with a healthy pay package. In addition, open source tools will continue to dominate the analytical landscape with a combination of R and Python being more in demand, than just the knowledge in SAS. These tools are popular with Big data and Machine Learning professionals equally.
It is interesting to note that big data has evolved from a simple descriptive analysis or clustering analysis to machine learning techniques. And thus enters Spark and Tableau, while Spark assists to run machine learning algorithms without much difficulty on large data sets, Tableau makes it possible to create powerful visualisations on data sets irrespective of the size.
Certain jobs with specific skill sets which were popular in analytics in the year 2017, continue to hold the ground and expand its scope, like….,
It manages to stay as one of the most popular skills, it is considered as the ability to apply critical thinking to interpret numbers and to use specific programming languages and tools to distinguish when patterns in data are meaningful so that actionable output can be suggested to the stakeholder.
Data Management is a skill relating more towards how the data is structured, with the restriction on access, and the knowledge of all the different approaches to storing data. A Database Administrator is a job that requires data management skills.
It is the practice of gathering information and insights from the database to make informed business decisions. Business Analyst, Business Intelligence Developer, Customer Insights Analyst are a few jobs which require the business intelligence skill set.
This is a process of collecting data from different sources, combining large amounts of data to enable analytics. These day’s data is collected from various sources by the companies and data warehousing lets it all sit in one place. A Data Engineer is a job that requires data warehousing skills.
With easy and affordable processing and storage facilities, the basic hurdles have been eradicated. Instinctive computing power is replacing traditional statistical models. And as we progress in the world of Deep Learning, Machine Learning, Artificial Intelligence, we will be placing more faith in machines, and to build such machines will need to adapt the skillset required.