Becoming a Data Scientist : A data analyst is a person who is capable/able to collect, to process and to perform some statistical analysis with the data available to him. This person needs to have skills which allow him/her to deal with software/programs such as Microsoft Excel, basic SQL, basic web development, ability to dive into a concentration and ability to conclude.
How to Become a Data Scientist ?
There are also some numbers of elements such as programming, statistics, mathematics, machine learning, data wrangling, communication & data-visualization and data intuition which we need to mention while speaking about data analyst. These elements are the things which make someone to become a professional and successful data analyst. They are the following:
- Programming, is one of the most important job done by the data analyst. It’s so important to the point that she or he needs to write programs or to use programs to end up at solution of problems which she or he is facing. He needs to have the knowledge of the programming software such as Python and others programming software. This programming is in fact even the part which differentiate a simple statistician and a data analyst.
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- Statistics is a useful tool while working with data because in any case when we are not 100% sure of the decision to take, we can rely on the available statistics and draw a conclusion to the problem or interpret the results to facilitate our lack of decision-making. Statistics is allowing us to see if all those different techniques are useful to us with the related cases or not.
- Mathematics, your basic mathematics learnt at high school or college need to come in action at this level. You may be ask to give an equation relatively to a specific problem and so on. So Mathematics and Statistics are kind of correlated, which means that you need to be good in calculating what you have to prove and do not forget that the statistics are behind what you want to calculate and demonstrate. A question of mathematics may lead you to bring in statistics and vice versa.
- Machine Learning, then we may look at the fact that we need some algorithms to solve our problems so the data analyst need to have that knowledge of run large amounts of data into the algorithms so that his work is simplified and he is able to make better conclusions. You may also need to create new algorithms if the one you have cannot process the data you wish to work on, that why you need to master your way to work with algorithms and large and big data provided or collected by you or someone else.
- Data wrangling, this is one of the method use by a data analyst which isn’t much pleasant for some because in this step, you need to collect all the data and put them apart for further use. This process is done manually which means it requires much of your attention and time. This step of data wrangling is a step which can be done while working with data, after the operations or even before starting the operation of working with the data. That why is quite a bit complicated process because it require your attention and concentration on the matter?
- Communication and Data Visualization. Communication is one of the biggest problem faced by many people while data visualization is the way you presenting the data or the techniques you displaying the data you in a significant manner where you capture their attention and them learn something new in you presentation. You may have the right ideas but if your communication skill is weak then you cannot go forward and try to convince people to join you in your race. The same with your presentation, usually stakeholders are not interested in the graphs, etc… But in what you have to give to them and make them understanding that the risk they are willing to take is worthy their time and money. So, in this part of the data analyst must be a well speaker so that he can easily present in a well-manner the findings he has discovered to people (stakeholders usually) who are interested so that investment can be made or any action can be taken.
- Data Intuition is a measure you taking to try to answer rights questions during an event and ignoring useless ones so that you maximize you time and money. For you to develop this quality, you need to work on many data as possible. This step help us to make use of our knowledge in presentation, interviews because we cannot in case answers a hundred questions in a conference for example, so we need to have the knowledge of data intuition so that we know what types of questions to respond to, which languages to use while responding even if we are of different view with the others members of the group on the subject/topic and who to respond to.
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Remuneration for Data Scientist
It’s obviously in this world that the job which requires much of your attention is also a most paid job. This applies to data analyst too. Since you need to work with big and large amount and have some special skills which are require by the industry, the remuneration of this job is perfect for someone doing this job and top companies in the industry offer attractive packages to attract best, skilled and professional data analyst in their nest.
Job Profile for Data Scientist
Data Analyst Job includes:
- Gathering and extracting numerical data,
- Finding trends, patterns and algorithms within the data,
- Interpreting the numbers,
- Analyzing market research,
- Applying these decisions back to the business.
- Gathering and extracting numerical data: you need to know how to gather the information you need and how to extract this information in a useful way so that they make sense otherwise you will have just loose hours to do a work which is useless and you will be ask to repeat the same work.
- Finding trends, patterns and algorithms within the data: At this requirement of your daily work, the data analyst needs to have a full knowledge of things which I have mentions above to make his work easy. This method helps him to achieve his purpose while working on the information and data available to him.
For you to find the trends among the data, you also need to know the direction how things are going so that you may withdraw if you are in the right direction or the wrong one.
This same rule is applying to the remaining of the patterns and algorithms. For you to write a good algorithm, when need to extract a data for example, you need to know how the previous was written and what didn’t work while using it so that you correct it when write a new algorithm to solve your problem and have a desire answer.
- Interpreting the numbers: When you come to interpret the numbers, you first need to know the digits numbers used for each numbers (from 0 to 9). Each number has a specially and number system attribute to him so if you do not how to read or even write them, you won’t be able to interpret the numbers in your situation and be fruitful in your work as a data analyst. An analyst has we all know is someone who is able to analyze, draw and conclude the solution needed in a problems and in case of an analyst, your analysis skill needs to be at the top.
- Analyzing market research: At this stage, as the word can states, “analyzing market research”, you need to have the knowledge of the market, how to analyze the market (this analysis need to be done in a different way to make a difference between you and others analysts or people in the same field and doing the same work), how to draw conclusions between facts, myths and reality, and all the strategies needed to be a great market research and specially a professional and best data analyst.
- Applying these decisions back to the business: All the strategies I have elaborated above need to be applying back in the business. In others words, you need to put them in action otherwise they will be useless for you to know all of them and won’t profited to your business or daily work to achieve your task.
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Education Qualifications for Data Scientist
As any normal work, you need to have some education requirements like a bachelor degree is require for an entry level and a master degree for the upper level entry. These degrees must be in field such as mathematics, computer science, statistics, and all other related fields. You need to know also that a strong mathematics and analysis are requires for the work.
As we all know that in any field, you cannot be the best in one day but you need hard working, patience, perseverance and passion of what you are doing otherwise you will never succeed. So to be a successful data analyst, you must first love numbers, like to take decisions (right ones) and be passionate about data analysis.
In a conclusion, I can say that data analyst is a person who is be dealing with some statistical problems all his life because it is his work of every day and he is been doing this for year and is able to work with some software which allow him to solve the problems he has faced. You must have all those qualities for to be a successful data analyst.