Why Every Organization Should Hire Data Analyst?

Why Every Organization Should Hire Data Analyst

Why wouldn’t you consider hiring a data analyst? Given the abundance of information and data that we have all around us, are you able to make sense with it? Or are you able to use it to your benefit for your and your organization’s growth? If yes, congratulations you’ve made an excellent choice! If not, then you may need to catch up to speed. This mere 10 minutes read, will throw light on why exactly will your organization need a Data Analyst.

Data Analytics is no more a foreign concept as few years back. Today, most of us know or at least have heard about Data Analytics. The tasks that are involved in the role of a Data Analyst may be esoteric for some however the advantages that this domain brings to your organization are quite visible and straightforward. It has been proven time and again that organizations that use extensive data analysis can beat the competition from time to time. There is a certain Toward Data Science Survey that states that more than 54% of organizations may need predictive analysis that generates business intelligence to stay relevant.

One of the commonly known reasons why Data Analysis can win over any business and support with continued revenues, is because it provides the organization with actionable and relevant insights on improving their business model. Organizations are also able to cut down on their operation costs, understand customer pulse, consumption trends and so on with Data-driven decision-making.

The role of a Data Analyst is to avail you of these benefits. Data Analysts are trained people who are empowered to offer you relevant business intelligence that has the potential to maximize your cash flow and improve your bottom line. Your business can achieve growth that is measurable and sustainable.

Let’s answer to the curiosity:

What is Data Analytics?

Before we understand the why of Data Analytics, let’s throw some light on what is Data Analytics and how is it useful to your organization. So to speak in the basics, Data Analytics deals with discerning meaning out of the disorganized information and giving meaning to the raw data that an organization may avail. It is data driven approach to decision making.

When you are able to understand, project, explore & strategize your abstract data, you are also able to make the right decisions. You can share valuable insights within your organization that are derived from giving meaning to data. Data Analysts are able to interpret the data viz numbers also called Quantitative Data, sounds, words or images also called Qualitative Data. These interpretations lead to solid conclusions and actionable insights which can empower your profitability and business’ bottom line.

Process Outline of Data Analysts

in very brief

To begin with Data Analysts use the very raw disorganized information available at the organizational/departmental/individual level. They take this raw data and come up with supportive information by implying certain interventions. They bring stability to the unstable raw data. To be able to make the data analyzable, the first step is to collect, organize and clean the data.

Next in the phase of data analysis there is deployment of multiple metrics to make sense of the data for decision making. Some of these metrics are statistics, visualization and programming. These days we have tools to automate all of these metrics easily. However despite of the increase in automation, Data Analysts need the tangible or intangible skills to move around the data eco system.

Why are we making a big deal out of Data Analytics?

Two powerful reasons why Data Analytics is so important:

Firstly, Data Analytics gives decision making power to an organization.

And secondly the nature of the data is evidence based which can give factual information.

Data Analysis give the organization the power to make decisions which are rooted in the empirical data. Out here it is important for us to note that Data Analysis may not give hundred percent accurate results, however it is great at predicting the future trends and come up with meaningful conclusions.

With Data Analysis companies have the power to be proactive in

  • adapting to the changing needs of the times
  • can mitigate the risks associated with uncertainty
  • being alert and not fall baits to frauds
  • understanding the needs of their target audience
  • delivering new products/ features on time
  • being able to customize their services to the needs of their consumers.

Without Data Analysis businesses work on instincts and not on tangible facts and evidences.

Let’s understand here that Data Analysis is just not limited to the businesses but its impact is widespread to the society at large. We are able to use the data to improve patient experience in hospital, apply this to the agriculture technology to make the most of seasons and food crops.

What magic can Data Analyst spell?


But they can make your data work magically for your organization!

Now that we have got an understanding of what Data Analytics is and why it can add value to our business let’s deep dive into what is the role of Data Analyst in your organization. The very primary role of Data Analyst is to be able to transform raw data into actionable insights for the key decision makers. After analyzing the data that is available at the organizational level, the Data Analyst is going to answer specific questions or solve specific problems that’ll support actionable insights. Once the Data Analyst have been able to solve the set of problems they are expected to provide evidence to their superiors who could plan for the future decisions to be made.

Briefly we could associate the following responsibilities to Data Analyst

  • Creating and implementing database and data collection system
  • Working closely with management/ key decision makers to identify KPIs, critical metrics and the business needs
  • Collecting primary and secondary data
  • Cleaning and applying necessary filters to data
  • Identifying patterns and trends in complex data systems and analyzing them
  • Present the findings to the stakeholders
  • Presenting the data in visual language
  • Building relevant reports
  • Customizing the reports and keeping them updated
  • Creating and upgrading Dashboards
  • Developing and maintaining documentation pertaining data models, infrastructures, measures as they keep upgrading

These are the responsibilities of Data Analyst broadly. Let’s look at some of the specific task that Data Analyst carry out to support your organization with visual, relevant and understandable Data.

What will Data Analyst do for your organization?

  1. Beginning with defining the question
    The Data Analysts come with skills to understand the problems that they are dealing with. Without this kind of understanding the raw data cannot transform into intel. What at times look like a very simple business problem with a possible solution may not be the problem at all. You may not reach the core of the problem without the support of data centric decision making. Data Analysts can analyze the problem in every way and come up with possible solutions They’d need to come up with unbiased advice that they give to their superiors and use the tools and metrics needed to reach to a decision.
  2. Collecting the raw data
    After the Data Analyst are able to understand the question at hand completely, they’ll begin with uncovering the raw data that may lead them to the possible solutions. Sometimes this data can be quantitative and some times it can be qualitative as well. It is the job of Data Analyst to understand where do they get the data from.
  3. Cleaning of the collected Data
    After your Data Analyst has been able to collect the data, it is still in the very raw form. This means that the data will need to be organized to gain insights from within it. Raw Data is erroneous. Data analyst will identify the data that needs cleaning and they will employ certain tools and technologies for the same like generic software, custom algorithms and exploratory analysis to bring the data to suitable state.
  4. Analyzing the cleaned Data
    After the process of cleaning and of validating the data the Data Analyst will conduct analysis of the present data. There are different kinds of Data Analysis and one of the challenges for Data Analysts is to identify which approach will they take. The Four approaches to Data Analysis are as follows:
    • Descriptive Analysis: Analyses what has happened based on the Dataset
    • Diagnostic Analysis: Here the Analyst tries to examine why certain things happened based on the Data at hand.
    • Predictive Analysis: As the name suggests this type of analysis is done to identify what will happen in future on the basis of the Data at hand
    • Prescriptive Analysis: With Prescriptive Analysis Data Analysts are able to identify the best course of action based on the Data
  5. Communicating the result of Data Analysis
    After conducting Data Analysis and drawing a conclusion, the Data Analyst will communicate the findings, results with the key decision makers. Here the analyst will present the data, mostly visually so that everyone on the team is able to understand and interpret the Datasets. Visualization may involve developing interactive dashboards, reports, documents and presentations.To be able to clearly communicate the analyzed data is one of the significant responsibilities of the Data Analyst. Without a very clear data presentation there may pertain some confusion which may create discrepancies while taking the best decisions within organization.

With Data Analysts Organizations are able to make the following informed decisions

  1. Evidence centric decisions: The decision makers within organization are expected to make big decisions that can bring changes and transformation. They need to have access to relevant data for the same. In larger organizations making decisions may take months or weeks. Even smaller organizations can make use of Data Analyst to make high powered decisions to improve the agility of the organization. Data analyst empowers key decision makers to make strategies with the context of concrete evidence based Data
  2. Retesting the decisions: Without the support of Data analysts there is no way an organization may know if the decisions that have been made work or do not work out. If you are not using data to measure the success of your strategy then maybe you are not making decisions on facts but are doing so on the basis of instincts and opinions. We’d need to test and retest our decisions to know if the organization is on the right track.
  3. Being Innovative: With data analysts, companies are able to remain one step ahead of their competition. You can analyze the consumer trends and behaviors and come up with your product and services that are more relevant to the users. With these innovative strategies organization can remain ahead.


Decision making in every stage of your organization can make or break the chances of running a successful business. If your organization has Data Analytics systems in place, you are automatically ahead in your niche, above everyone who is not using these metrics.

With Data Analytics you can plan for the future obstacles, make relevant strategies, cut operational costs, streamline the production process, reach to your end consumers more efficiently and quickly. Data Analytics can bring these into play to support you towards your vision.

Vikas Agarwal is the Founder of GrowExx, a Digital Product Development Company specializing in Product Engineering, Data Engineering, Business Intelligence, Web and Mobile Applications. His expertise lies in Technology Innovation, Product Management, Building & nurturing strong and self-managed high-performing Agile teams.

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