“Data Analytics is a precious thing and will last longer than the systems themselves”
– Tim Berners Lee, Founder, World Wide Web
A data analytics expert gathers, processes and executes statistical analyses over massive datasets. They explore the ways how data can provide solutions and answers to all the questions. Computers are advancing each day. The systems are moving towards technological entwine, which is evolving data analysis as well. Relational databases are developing, which is helping data analysts reach new heights. The introduction and prominence of Standard Query Language or SQL allow the analysts to fetch data in half the time from databases.
The day-to-day job description of a data analyst largely varies depending on the company or the industry they work in. Each industry specialises in different processes, and each process demands a different kind of workflow.
Data analysts are proficient in handling the business intelligence softwares like SAS, PowerBI, Tableau, etc. They work hand in hand with the IT Team and the data scientists, following organisational goals. Data Analysts mine the data as well as clean data while analysing from primary or secondary sources. They use statistical tools to pinpoint correlations, patterns, and trends of complex datasets. Senior data analysts also need to make reports based on their findings and communicate them to the stakeholders or management.
On that note, let’s look at ten skills you must hone to be an efficient data analyst –
1. Programming Language Proficiency
It is a must for every data analyst to be proficient in at least one programming language. Knowledge of multiple programming languages is always welcome, but they cannot analyse data without knowing one. They often use SAS and SQL tools to gather, analyse, and visualise data.
2. Analytical Thinking and Creativity
The two elements defining the attributes of a good analyst are creativity and curiosity. It comes in handy to have a strong knowledge of statistics, but their critical thinking ability is the factor that cuts them above the rest. An analyst who thinks about solving a problem with a creative approach comes up with more interesting questions. A detailed analytical report and questions enhance the company’s image of how well they can deal with matters at hand.
3. Communication Skills
It is the data analyst’s responsibility to communicate their findings. In addition, they need to convey to executives who make strategic decisions based on those findings or maybe to a reader. So, honing their communication skill is also crucial for them.
4. Data Visualisation
Data visualisation is not possible without a few trials and errors. A good data analyst must know how to visualise and present findings to the end readers. So, they must know what scales to use, what graphs to make and which chart to refer to depending on the target audience.
5. Data Warehousing
Data Warehousing means storing vast volumes of data which helps the company to make management-level decisions. Some data analysts also work from the back ends. They work to create a data warehouse by connecting databases from numerous sources. Query languages help in data warehousing, which helps in finding and managing those data.
6. SQL Database
The data analytics team must be well versed in Standard Query Language. SQL is one of the most used tools in this field due to its relational database full of structured data. In addition, it acts as a repository of data, helping analysts draw information to carry on with their analysis.
7. Database Query Languages
Data Analysts prefer SQL as the most preferred querying language. There are multiple variations of SQL in the market like –
The better an analyst can learn these, the better they can analyse data.
8. Data Mining and Data Cleaning
Raw data doesn’t get stored in a database directly.
9. Microsoft Excel
As a student, we often undermine the vast potential of the humble Microsoft Excel. Microsoft Excel can do the most advanced calculations of statistics with the correct formulas. A good data analyst must have a good understanding of advanced MS Excel along with advanced modelling techniques.
10. Machine Learning
Data analysts who have machine learning skills are valuable in organizations. Machine Learning is not technically the topmost skill set that companies look for in an analyst. However, possessing that skill set comes as an advantage that leading organizations prefer.
So, how is it to be a data analyst? It entirely depends on where they are employed and what tools the company works with. Several organizations do not even use any programming languages. Microsoft Excel and statistical software do the job for them. This again depends on the type of problems they aim to solve. The data analysts sometimes perform the tasks of data scientists as well. They write the queries during the daytime and develop customized solutions with a relational database using Hadoop or NoSQL.
Steve Taylor worked with a leading multinational IT firm for twenty years before taking a sabbatical. Currently, he is associated with MyAssignmenthelp.com as a senior writer assisting students with IT-related essays and provide Information Technology Assignment help to students also Outside work, fishing is his favourite pastime.