The world is searching for data scientist Skills but it appears there just not enough of them. The unsurpassed number of data scientists required each year is way ahead of the number of data scientists produced by the industry. If you are anywhere related to data sciences, big data, and numbers, this post is for you.
Data Scientist Skills:
To start with, numbers must be your companion. You must know how to use numbers for coding, conducting statistical analysis, and presenting numerical information for the end-user to understand.
Some important languages to reckon with are Java, R, Python, and C++. It’s not mandatory and not even possible to learn all the programming languages but everyone expects you to have some basic knowledge of some important ones.
#Data structure and algorithms:
A career in big data entails you to have knowledge of algorithms as well as data structures which in turn will make other information indispensable. Those are data types (bags, queues, and stack), data structures (red-back trees, binary search trees, and hash tables), sorting algorithms (heapsort, merge shot, and quicksort), and Big O.
There are a lot of ways you can build your analytical skills like playing chess and online puzzles. If you already have an analytical bent of mind, nothing can be better than that.
You are required to handle a large set of data. SQL is your go-to when you are involved in solving a large set of data. It is extremely beneficial in sorting things out.
If you have specialized in mathematics especially the subjects of linear algebra and calculus, it would be very easy for you to understand probability, machine learning, and statistics.
Apart from programming, there is a range of technologies you must be aware of to build your data scientist skills. Some of the basic tools are SQL, R, and Microsoft Excel. After you have become skilled at these, you can think of other credentials like Cognos, MatLab, SAS, and SPSS. Alternatively, think of having big data certifications in Scala, Python, Linux, Spark, and Hadoop.
The open-source resources on big data technology are mostly written in Java, so you are supposed to know it too. A technical mindset will help you in tackling Hadoop for Spark. You must be able to solve the three languages of Scala, Python, and Java. Java and Scala are the preferred languages. Spark is gaining a lot of popularity these days because of it being fast.
Scala is used to write Spark. Because the latter is more functional in programming. It is also compatible with Spark APIs and its Resilient Distributed Dataset (RDD) of Spark. Consequently, Spark libraries updates come beforehand for Scala.
Python is popular for text analytics. It offers a strong foundation for support in big data. Generally, having big data certifications will open a new door of opportunities for you. For people involved in the scripting of big data, it is a requirement to have Python credentials.
Data scientist skills are not complete until you have the most important skill of them all- to analyze. When you just compile data in a stack without using them for effective planning and administration of business functions, it’s as good as not having the data at all. That’s what good big data certifications will help you understand.
An Additional Overview:
There are a lot of news making rounds around the world on the topics of AI, big data, internet of things, and wearable technologies. It’s our choice whether we want to make big data the next nuclear bomb or the next therapy.