Raw data is often more meaningless to people and most of the organizations because it makes it hard to find the availability of meaningful information from the data. To enable different people find a meaning out of the data that they have, data analysis is one of the most interesting areas that can be of great benefit. Through a detailed analysis of the data, people can come up with meaningful insights from the data that can help them in different areas, in relation to the data.
WHAT DATA ANALYSIS INVOLVES
Data analysis involves a wide range which starts from collecting the data, finding insights about the data, cleaning the data to remove unwanted ones, and finally modeling the data in a perfectly presentable way to allow different people get to see what the data represents. A clearly analyzed and presented data helps in positive decision making in areas such as businesses, health sectors, artificial intelligence, business marketing and much more. For example, given the data for a companies sales over a year, you can use different tools to find the areas of performance and areas that led to loses within the organization. The following are some of the tools that are useful in data analysis:
- Python Python is one of the mostly used programming languages in the world and is mostly known because of it's ease of use and adaptability in different fields. Python programming can be used in data analysis due to the huge number of libraries. Data analysis involves different sections to come up with a final analyzed data and this is why python is of great importance. It has a number of libraries that can be used in the process of development and here are some of them:
Numpy
it is mostly used for when calculations are needed in the data to make the data in a more readable format and an easy to understand way.Pandas
To handle the data, this library is of great importance as it helps in manipulating and understanding more about the data. it includes a number of mathematical computations.Matplotlib
This library helps in visualizing the data from creating charts, building graphs, most of which are much interactive and allows users to interact with them.
SQL
This is one of the most important tools for any data analyst. As a data analyst, you mostly interact with data and learning how to handle the data is important for you to give insights about the data. In most of the organizations, the data and information are stored on some databases. SQL is a query language which is used for getting the data from the database, cleaning the data before using some visualization software to present your data.Excel
After getting insights about your data, you need to give a high level overview of some of the information that you learn from the data. Excel is one of the important tools that are used to create charts of ones, choice, and the charts can be then passed into a dashboard for presentation. It includes a number of tools from Pivot tables to statistical computations that are used in the process. Not only is it used for data presentation, but it also gives an opportunity to clean your data, remove some unwanted fields or empty columns. Mastering Excel is one of the important steps to take as a data analyst.Power BI
There are different analytics tools that can be used and Power BI is one of them. It basically is a tool which allows for analyzing data and creating interactive visualization where users can interact with the charts, filtering the sections they want enabling users to create some dashboards which they want through easy steps.Tableu
Just like Power BI, Tableu is used to create some interactive dashboards in easy steps. It makes work easier due to its integration with some data sources such as the sql and NoSql databases. Its easy interface makes it one of the most used data presentation software as compared to other visualization tools.
CONCLUSION
For one to perfectly master data analytics, a perfect familiarity with the tools and the techniques used in the process is necessary. Understanding the type of analysis needed from you whether it is a predictive analysis or an Exploratory data analysis is important to be able to deliver what is expected anytime a data analysis task is given to you. A perfectly analyzed data is more effective in coming up with
solutions to problems, giving suggestions of different sectors, increasing a companies performance and much more. Achieving this can only be successful through having a , mastery of SQL for data storage, retrieval and manipulation, python for data manipulation, data cleaning and data presentation, Tableu or Power BI for creating interactive dashboards and charts.
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