Is Data Scientist & Data Analyst are same? Learn the Differences Now!


If we talk about the hottest jobs in tech right now, then only two names will pop up in your mind those are a data analyst or data scientist. And, that’s not only we are saying even the Harvard Business Review declared “data scientist” as the“sexiest job of the 21st century.” But there is a lot of confusion between both the names even people who have some basic knowledge of data science consider both the job profiles as one.

  Well, the reason behind this confusion is both of the professions deal with big data, rather defined vaguely and sometimes used interchangeably with one another.

difference-between-Data-science-and-data-analyst

So, here we are to explain the differences between the two of them and that too in the easiest way. Let’s begin the brief introduction of both the terms, followed by skillsets each require to understand well. 

Definition

a. Data Analysts


Data Analysts play a vital role in the Data Science domain. As a role, they play a variety of tasks associated with collecting, organizing data and getting statistical information out of it. Besides that, they also showcase the data in the form of charts, tables, and graphs and use the same to build relational databases for organizations. There are various other fields and titles which are associated with Data Analyst job roles such as Data Architects, Analytics Engineer, Database Administrators, Operation Analyst, etc.

You may also like Data Science Training in 130 hours 

 http://www.asterixsolution.com/data-science-training-institute.html

b. Data Scientists


On the other hand, a data scientist, make predictions which further assist businesses to make critical but correct decisions. However, as Data Scientists are proficient in statistical, mathematical, and computer application skills too they can perform almost all the tasks a data analyst used to do. Moreover, they are the ones who are effective in selecting and solving the relevant problems that can help a business excel.

Skills

a. Data Analyst 


Top skills a data analyst hold is basic math know-how, understanding of algorithms, good communication skills, knowledge of software engineering, programming languages like Python, SQL, R, JavaScript & HTML, Spreadsheet Tools (Excel) and Data Visualization Tools like Tableau.

60 Hours Python & Machine Learning training with Live Project.

http://www.asterixsolution.com/python-machine-learning-training.html

b. Data Scientist


Like a Data Analyst, a Data Scientist also has basic math know-how, good communication skills, understanding of algorithms, and knowledge of software engineering. But being expertise in the job the skillset of a Data Scientist also requires a knowledge of programming languages like Python, SAS, R, Matlab, Pig, SQL, Scala, and Hive, Business Acumen, Story-telling, and Data Visualization, Distributed Computing frameworks like Hadoop and Machine Learning Skills.

  We can say the strong foundation of acumen along with the ability to communicate the findings in the form of a story to both business stakeholders as well as IT leaders is something that differentiates a data scientist from a data analyst. 

On a concluding note, we have seen enough that differentiates the two hottest IT professions in the big data world. Regardless of the differences and similarities between a data analyst and a data scientist job roles, one is incomplete without the other. And, this is the best time to master any of them and get started in Data Science domain. 




www.asterixsolution.com | +91 9769688926

Location: Thane, Maharashtra, India

Comments

  1. Cognex TechnologyAugust 3, 2020 at 12:18 AM

    Cognex providing AWS Training in Chennai

    Here, you will learn how cloud computing is redefining the rules of IT architecture, like how to design, plan, and scale the AWS platform.

    ReplyDelete

Post a Comment

Popular posts from this blog

Why, when and how to return Stream from your Java API instead of a collection

Introduction Collections are basic and commonly used data structures. Programmers from the beginning of their career learn how to use them to receive, process and return data. Getting more advanced in Java programming, they find stream() method to convert a collection into a stream and learn how to process data using some of the stream’s useful methods like map, flatMap or reduce. They could also notice that other APIs in Java return a stream too e.g. String.lines(), Matcher.results(), Files.find(), Random.ints(). If you have experience with consuming streams but haven’t produced them yet, this article is for you. I’m going to show you some scenarios where streams can be very convenient and examples on how to use them. Additionally, I shortly mention error handling and resource management. The article is based on standard Java library java.util.stream. It’s related neither to reactive streams nor to other implementation of streams like e.g. Vavr. Also, I’m not going to cover a
Read more

What is Kubernetes?

Kubernetes (also known as k8s or “kube”) is an open source container orchestration platform that automates many of the manual processes involved in deploying, managing, and scaling containerized applications. In other words, you can cluster together groups of hosts running Linux containers, and Kubernetes helps you easily and efficiently manage those clusters. Kubernetes clusters can span hosts across on-premise, public, private, or hybrid clouds. For this reason, Kubernetes is an ideal platform for hosting cloud-native applications that require rapid scaling, like real-time data streaming through Apache Kafka. Kubernetes was originally developed and designed by engineers at Google. Google was one of the early contributors to Linux container technology and has talked publicly about how everything at Google runs in containers. (This is the technology behind Google’s cloud services.) Google generates more than 2 billion container deployments a week, all powered by its
Read more

Best way to learn Java programming

Having said that I am writing this post dedicated to all my young (or I should say beginner) fellows who want to attain a certain level of proficiency in java technology and somewhere would like to take my advice on this. Keep in mind that if you do not like the way to learn java, I am proposing in this post, then just ignore me. Period. OR better, suggest me what you think is the better way to learn java fast or easily. Here I am assuming the people reading this post will be, who are very new to language, so I will start by listing first thing first. Make sure you have prepared your Java development environment ready i.e. You have installed JDK/JRE and you have an IDE like Eclipse. 1) Learn the language basics This is the first step for very obvious reason. If you don’t know the basics then you will never know either what to do next or what you are doing wrong. Initially, I do not expect from you to become the master of all java basic stuffs like keywords, core concepts o
Read more