Data analysts translate numbers into plain English Every business collects data, whether it's sales figures, market research, logistics, or transportation costs. A data analyst's job is to take that data and use it to help companies make better business decisions. This could mean figuring out how to price new materials for the market, how to reduce transportation costs, solve issues that cost the company money, or determine how many people should be working on Saturdays.
There are many different types of data analysts in the field, including operations analysts, marketing analysts, financial analysts, etc
A bachelor's degree is needed for most entry-level jobs, and a master's degree will be needed for many upper-level jobs. Most analysts will have degrees in fields like math, statistics, computer science, or something closely related to their field. Strong math and analysis skills are needed.Depending on the field you go into, certification is available.
- Math (e.g. linear algebra, calculus and probability)
- Statistics (e.g. hypothesis testing and summary statistics)
- R and/or SAS languages
- SQL databases and database querying languages
- Python (most common), C/C++ Java, Perl
- Machine learning tools and techniques (e.g. k-nearest neighbors, random forests, ensemble methods, etc.)
- This list is always subject to change. I believe generic programming skills are a lot more important than being the expert of any particular programming language.
Analytic Problem-Solving: Approaching high-level challenges with a clear eye on what is important; employing the right approach/methods to make the maximum use of time and human resources.Effective Communication: Detailing your techniques and discoveries to technical and non-technical audiences in a language they can understand.
You can learn Data Science online with the various courses that are offered but I believe a fresher should always go for a blended course which gives classroom training to acquire the right knowledge, industry exposure to learn the skills and build a network and online practical learning.Pick up a project on Kaggle or Hackerearth and start learning R, Python or any other tool. You'll start learning things gradually. Start from small eventually you'll end up big. All the best. Make a portfolio of projects that you do with the code, visualizations, analysis in words, conclusions, thoughts and everything around that project.
Here are Some of the courses that can help you master the concepts required for getting into Data Analytics
There is no one size fits all solution. Your situation could be different (educational background, experience etc.), this is where experts and mentors from Data Science field understand your profile better and guide you in the right path.
Like what Suzy Welch says "Your mentor doesn't need to have seniority over you." A mentor just has to do something better than you do.Here are some of the experts who are willing to help you achieve your career goals. They conduct a personal one–to–one over Skype and discuss your profile and areas for improvement.
- Ujjyaini Mitra (Specialist: Data Science, Career movement to Data science)
- Mario Lewis (Specialist: Data Science, Big Data and Analytics)
- Jose Munoz Mata (Specialist: Data Science, AI, Career Development)
- Harpreet Dua (Specialist: Data Science, Business Analytics)
- Ganapathy Govindan (Specialist: Data Science, Big Data)
- Arihant Jain (Specialist: Data Science, Predictive Modelling)
- Anmol Sunsoa (Specialist: Shaping future in Data Analytics)
To all fresh grads and Data Science enthusiasts, I hope that you find my article useful and you’ll have a good start in your search for a Data Analyst job in 2018. You can post your comments below to discuss on the points that I have highlighted in this article.