Data Analyst vs Data Scientist vs Data Engineer vs Data Visualization

Today we are going to discuss the difference between various designations which are hyped now a days. Students or people are confused about what they want to be or what they should learn? Today we are going to tell you the actual picture which you will find in organizations.

Business Problem

All organizations are working to make profit and they started their operations some time ago. They have huge data stored in their system (database, websites, SAP, ERP and more). Now what they will do with that data which they have stored?

Let me first explain with simple example. Suppose you started your small retail store in 2010 in some area in xyz country. Now whenever customer will come to buy anything, you will save the sold item details, customer details somewhere to keep track of your sales. (if you will not save anywhere you will forget everything and how you will judge whether you are making profit or not? How you will file tax? and how your store balance sheet will be created?) Now suppose after 10 year you have stored data of previous 10 years. And by the time you see a new store also opened in same locality. So, what you will do now in this competitive environment.

You can take various proactive action to make profit and attract your customer as below.

1. You can send your customers Birthday wish, Anniversary Wish which will make your customer happy and they will remember you.
2. You can find customer purchase pattern and send them notification about discount and sale going in your store.
3. You can maintain your store inventory ready for customer because if customer comes to your store and he/she doesn’t find products which they are looking to buy then they will go to another store and say that your store always lacks of product which they want to buy. Your saved data having history of everything and you can predict the demand and order inventory.
4. You want to see which product make you more profit. Which customer is purchasing more items as he is good for you?

Whatever I explained above is applicable to any organization because your store is also small organization.

What we need to do in company?

  Now to send any communication about birthday wish and anniversary wish we need to find the customer data. Same way to send sale or discount offer notification we need to find which customer buy what kind of product? We cannot send laptop discount offer to customer who buy grocery items only.

  All organization’s data is stored in database whether they have website, SAP, ERP or any other type of software. Database is like notebook. We write everything in notebook same way digitally data is saved in database. If you are thinking what does Data means. Data is any information like our name, age, mobile number, address. Same way for company data can be customer details, product details, sales details and purchase details etc.

Why we need people working with these designations?

As we have discussed, data is stored in database therefore we need to have required insights from data to perform any proactive action.

Now big question comes who will find data insights from database and give us insights which suits our business. Even after finding data who will transform that data as per required business form. And How we need to interpret the fetched data.

Here mainly three types of tasks are performed in any project

1. Fetching, processing data and finding current insight from data (Data Analyst)
2. Finding future pattern which does not exists in data (Data Scientist)
3. Make data presentable, created in above 2 steps (Data Visualization)

Fetching, processing data and finding current insight from data (Data Analyst)

Fetching, processing data and finding insights are done by Data Analyst. Please don’t be confused. Data Analyst is just a designation here. I am trying to tell you how usually it goes in any project. We can say that this is the task of a Data Analyst because by job role Data Analyst is guy who is having good knowledge of data fetching techniques from database like SQL Server, Oracle, My SQL and Teradata etc. After fetching data, he is having good knowledge of transforming data to desired business form with the help of Analytics tool such as SAS, R and Python.

Data Analyst will fulfill below business case which we discussed earlier

1. 1. If you want to send birthday or anniversary wish as we discussed earlier
   2. If you want to send the discount offer based on customer buying pattern

Finding future pattern which does not exists in data (Data Scientist)

  If you want to maintain the store inventory then you cannot blinding order anything by your heart because if you will order excess products then demand then those products will be lying in your store and vice versa if you will order lesser product to maintain inventory then you customers will go to another store without buying anything which is also your loss again.

  Here we need some solid trick to help us know the number of all types of products to be maintained in store as inventory where situations are manageable. This task is done by applying the statistics. Some people say applying Machine Learning. Everything is same just different name. As we can call car as vehicle as well.

  For Retails stores, pre-season demand forecast and in-season demand forecasts are done with the help of Machine Learning/Time Series Forecasting techniques which is nothing but statistics technique only. This is task of Data Science kind of role that is why people say Data Scientist. But it does not mean person with Data Analyst designation cannot work on Data Science work. It will depend on your knowledge; these are just designation given by company. Please do not confused by role and designation. A single person can perform both role if he/she has knowledge. Same way having designation of Data Scientist is waste if you do not have knowledge. Some organizations even do not give Data Analyst or Data Scientist designations. They give Data Engineer, Machine Learning Expert, Analytics Analyst/Consultant/Manager and more other types of other designations.

  Statistics and Machine Learning Techniques also applied on data with the help of SAS, R and Python only therefore person who want to work as Data Scientist role must have knowledge of statistics and these tools SAS, R and Python. Some companies also use SPSS, Matlab etc. but those are not widely used. Therefore, only SAS, R and Python are used more than 97% companies.

Make the data presentable create in above 2 steps (Data Visualization)

  Now task completed by Data Analysts and Data Scientists role need to be presented to business owner or decision maker. They do not know programming like SAS, R and Python. Same way business users do not have knowledge of statistics and Machine Learning. They understand only simple self-explanatory graphics like Pivots, Charts etc.

  Just to summarize we can say that we need to visualize data. This task is done by guys who are having good knowledge of visualization software such as Tableau, Power BI, QlikView, QlikSense, Excel and more.

  Data Visualization is finishing line of any project and is also end of tasks completed by Data Analyst and Data Scientist.

Skills required

Data Analyst job role

  SAS, R and Python. Combination of SAS + R or SAS + Python is good. Data Analyst must have good knowledge of SQL queries as well because it is the method of fetching data from database. Data Analysts should have knowledge of Excel too because there are lots of scenarios when you need to use Excel. You cannot go to SAS, R or Python for small tasks.

Data Scientist job role

  Data Scientist must have knowledge of basic statistics, Machine Learning techniques with SAS or R or Python because whether it is requirement of applying basic statistics or machine learning, they will have to use any one of SAS, R or Python as per business requirement.

Data Visualization job role

  Data Visualization Analyst prepare the dashboards in any tool (Tableau, PowerBI, QlikView, QlikSense, D3.js, Excel and many other) as per business requirement. Tableau and PowerBI are tending more now a days.

Project Phase

Any project in any company can have two to three phase which are completed by Data Analyst then Data Scientist (if required) then Data Visualization Analyst.

Data Analyst is job role which is must for any project. No project in the world can be completed without this job role because they start projects and process data and make it ready as per further requirement. Data Analyst role require around 70% to 80% time of any project

Data Scientist job role depends on project to project. Some project does not require this kind of job role. Everything depends on requirement only. Data Scientist job role is required around 10% to 15% time of any project if required.

Data Visualization job role is also crucial job role because whatever task we are doing, is been performed for client therefore we need to prepare reports or dashboards which are presentable and understandable by business users. Data Visualization job role is required around 20% to 30% time of any project.

What job role you should prefer while searching for job

Don’t be confused by designations such as Data Analyst, Data Scientist, Data Engineer, Machine Learning Engineer or Expert, Analytics Analyst etc. You must see the roles and responsibility. All organizations mention job roles as below

1. Should have good knowledge of RDBMS
2. Should have knowledge or working experience with huge data and multiple data sources
3. Should have knowledge of SAS, R or Python
4. Should have knowledge of Machine Learning, Regression, Logistic Regression, Time Series forecasting, Decision Tree, Random Forest, Deep Learning
5. Should have knowledge of Tableau or Power BI (anything preferred)

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