How Can You Build An Effective Analytics Team?

There is no doubt that every business thrives with the support and certainty of data.

Where collecting the right data and analyzing it can give you crucial insights into your business and help you for:

  • Taking well-informed decisions.
  • Discovering the popular trends of the market and your own customers.
  • Predictive analysis of business performance and expected revenues.
  • Identifying the bottlenecks of your business.

In today’s technological world, we have many kinds of data available. Some more relevant than others but it all depends upon its presentation and analysis.

Analytics team members are doing data analysis

Good data analysis takes a lot of organization and special skills which cannot be one person’s contribution alone and thus, requires a designated team.

So if you want to make your business more data-driven with a competent data analytics team, you will require the following skills:

1. SQL (Structured Query Language)

While companies can set up analytics training for their employees, some of the skills that are crucial for good analytics can only be achieved through practice and experience. One such skill is SQL.

In the Analytics world, SQL is considered one of the most prized skills that an analyst can possess. This is because in the industry which works with hefty data sets, working with Excel alone does not suffice the need and SQL is more suited for such areas. It can store, manage and relate data of multiple databases with ease.

Microsoft Excel on a tablet PC

2. Excel

Microsoft Excel is not just a table making tool but rather a powerful analytics system which is great for big datasets. Under advanced Excel functionalities, you can employ macros and VBA lookups for creating quick yet strong data analytic tools. In fact, if you are associated with a startup that is still in its initial stage, then it is highly likely that all of your databases are created in Excel only.

It has been decades since microsoft’s spreadsheets have maintained their stature in the business world and remained the most trusted platforms used for business development.

3. Data Visualization

Presenting raw data to establish a finding is never enough. For making a strong impression, one must possess the skills of representation and interpretation of data as well. Sifting the useful figures out from the flux is crucial in order to tell a compelling story to your audience and make a strong point.

Good analytics companies use high-quality charts, diagrams and graphs to visually represent data in a presentation for the attendees to clearly visualize the trends.

This kind of data presentation makes a lasting impact and makes the information easy to retain.

4. Python or R (Statistical Programming languages)

To put it simply, anything that Microsoft Excel is capable of doing, Languages like Python and R can do in a much better way. These powerful languages are used by analysts for advanced analysis such as in the case of big data analytics or for predictive analysis.

To understand it in a better way, you can assume that SQL makes up only the fundamentals of data analysis. For reaching an advanced level of data sciences, one must go beyond SQL and towards Python and R.

To make it easier, both, Python and R easily accessible, open-source languages which are available to programmers for free. Many programmers/data analysts choose R over python because it was specifically created for the purses of complex data analysis.

Machine learning algorithm

5. Machine Learning

This is the cherry-on-top skill for data analysts. In today’s world where we are rapidly progressing towards Artificial intelligence, learning machine learning and being able to use it for data analytics is a desirable skill.

If you have a team which can collectively bring together the above-mentioned skillset, you can build a strong data analysis team for your business and reap all the possible benefits or data science.