Skip to main content

Career in analytics these 3 are top tips you need

There is a big question to be successful in analytics career. I am giving most popular ideas to be successful in this analytics career.
tips on analytics career
Gettyimages.in
There are absolutely three...
The tip number one is you need to be familiar with different types of analytics.
  1. Web Analytics
  2. Financial Analytics
  3. Marketing Analytics
  4. Education Analytics
  5. Retail Analytics
  6. Health Care Analytics
The second one is you should have right kind of training at less expensive way.

In the booming Analytics Industry, one needs right course of training and experience, and working experience of case studies on selected analytics area, really boost your career. I am sure Udemy is offering lot of courses.

The third rule and idea is correct mindset

Assertive Communication 

BE PROACTIVE - Be Proactive is about taking responsibility for your life. You can't keep blaming everything on your parents or grandparents. Proactive people recognize that they are "response-able." They don't blame genetics, circumstances, conditions, or conditioning for their behaviour. They know they choose their behaviour. Reactive people, on the other hand, are often affected by their physical environment. They find external sources to blame for their behaviour.

Time management

PUT FIRST THINGS FIRST -What are "first things?" First things are those things you, personally, find of most worth. If you put first things first, you are organizing and managing time and events according to the personal priorities you established.

Positive thinking


THINK WIN WIN -Win-win sees life as a cooperative arena, not a competitive one. Win-win is a frame of mind and heart that constantly seeks mutual benefit in all human interactions. Win-win means agreements or solutions are mutually beneficial and satisfying.

Video on 7 habits of effective people

Comments

Popular posts from this blog

R Vs SAS differences to read today

Statistical analysis should know by every software engineer. R is an open source statistical programming language. SAS is licensed analysis suite for statistics. The two are very much popular in Machine learning and data analytics projects.
SAS is analysis suite software and R is a programming language R ProgrammingR supports both statistical analysis and GraphicsR is an open source project.R is 18th most popular LanguageR packages are written in C, C++, Java, Python and.NetR is popular in Machine learning, data mining and Statistical analysis projects. SASSAS is a statistical analysis suite. Developed to process data sets in mainframe computers.Later developed to support multi-platforms. Like  Mainframe, Windows, and LinuxSAS has multiple products. SAS/ Base is very basic level.SAS is popular in data related projects. Learn SAS vs R Top Differences between SAS Vs R Programming SAS AdvantagesThe data integration from any data source is faster in SAS.The licensed software suite, so you…

Blue Prism complete tutorials download now

Blue prism is an automation tool useful to execute repetitive tasks without human effort. To learn this tool you need the right material. Provided below quick reference materials to understand detailed elements, architecture and creating new bots. Useful if you are a new learner and trying to enter into automation career. The number one and most popular tool in automation is a Blue prism. In this post, I have given references for popular materials and resources so that you can use for your interviews.
RPA Blue Prism RPA blue prism tutorial popular resources I have given in this post. You can download quickly. Learning Blue Prism is a really good option if you are a learner of Robotic process automation.
RPA Advantages The RPA is also called "Robotic Process Automation"- Real advantages are you can automate any business process and you can complete the customer requests in less time.

The Books Available on Blue Prism 
Blue Prism resourcesDavid chappal PDF bookBlue Prism BlogsVi…

Top Differences Read Today Agile vs Waterfall model

The Agile and Waterfall both models are popular in Software development. The Agile model is so flexible compared to waterfall model. Top differences on Waterfall vs Agile give you clear understanding on both the processes. Waterfall ModelThe traditional model is waterfall. It has less flexibility.Expensive and time consuming model.Less scalable to meet the demand of customer requirements.The approach is top down. Starting from requirements one has to finish all the stages, till deployment to complete one cycle.A small change in requirement, one has to follow all the stages till deployment.Waterfall model creates idleness in resource management. Agile ModelAgile model is excellent for rapid deployment of small changesThe small split-requirements you can call them as sprintsLess idleness in resource management.Scope for complete team involvement.Faster delivery makes client happy.You can deploy changes related to compliance or regulatory quickly.Collaboration improves among the team.