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3 Top Books Every Analytics Engineer to Read

Many of the analytics jobs nowadays are for the financial domain. The top financial domains are Banking, Payments, and credit cards. 
The Best Books are on:
SASUNIXPython

The skills you need to work in data analytics are SAS, UNIX, Python, and JavaScript.  I have selected three books for beginners of data analysts. 

1. SAS best book 
I found one best book that is little SAS. This post covers almost all examples and critical macros you need for your job.

The best-selling Little SAS Book just got even better. Readers worldwide study this easy-to-follow book to help them learn the basics of SAS programming.

Now Rebecca Ottesen has teamed up with the original authors, Lora Delwiche, and Susan Slaughter, to provide a new way to challenge and improve your SAS skills through thought-provoking questions, exercises, and projects.
2. UNIX best book
The basic commands you will get everywhere. The way of executing Macros or shell scripts is really you need. This is a good book so that you can automate…

Resume: How to Show Data Science Project

In any project, the Data analyst role is to deal with data. The data for data science projects come from multiple sources. This post will explain how to put in a data science project in Resume.

Resume templates for software developers


Data Science project for Resume

The first step for an interview of any project is you need Resume. You need to tell clearly about your resume. 


In interviews, you will be asked questions about your project. So the second step is you need to be in a position to explain the project.

The third point is you need to explain the roles you performed in your data science project. If you mention the roles correctly, then, you will have a 100% chance to shortlist your resume. Based on your experience your resume can be 1 page or 2 pages.

How to show Technologies used in Data science projects
  • In interviews, again they will be asked how you used different tools to complete your data science project.
  • So, you need to be in a position to explain how you used different options present in the tools. Sometimes, in interviews, they may ask about the specific role in Tools specifically you used. You should be in a position to answer these questions too.

How to Prepare Resume

  1. Write a clear description
  2. Write a specific role
  3. Explain Tools
  4. Write about data flow

1. Write Clear Description

In any data science project, you will find a few things like Client name, the expectation of the client, and what you are going to deliver. These things you need to present clearly in Resume.

2. Write Specific Role

To convince your interviewer, you need to tell about your team roles and your specific role. In general, you can find the following roles.

  • Architect
  • Data scientist
  • Business Analyst
  • Development team
  • Testing Team
  • Integration testing team
  • Production release team

3. Explain Tools

You need to present all the Tools your project is using and your specific tools. Then, in the face to face interview, you need to tell what options you used to achieve what.

For example, I used some integration tool, to receive data to the development region, and to send out after unit testing.

If you explain, these key points, I can say, 100% sure, you will be selected.

4. Write about data flow

You need to explain how data is coming, is it in the sequential data set or document data. Something you need to tell clearly.

You also need to tell, after unit testing, which forms you will send the data to the next region. If you know this flow correctly, then you can convince easily your interviewer.

Also, Read

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