Let us look into what goes into a Data Analyst Resume. Before that, let us understand who is a data analyst. The information age started with people possessing scientist level skills, operating complex computing machines, and writing lengthy batch processing jobs. These were specialist jobs, requiring a computer science degree, post-graduation, or even Ph.D. With innovation in technology, the more creative tasks went up the hierarchy. The data analyst role is a middle-tier role, sandwiched between data loading or ingestion and data systems architect roles. The data analyst role requires a fair bit of analytical thinking to make sense of the underlying data architecture and the raw data it holds.
This role requires one to interpret data and turn it into information for the business to make informed decisions. It also requires a data analyst to be able to get data from various sources, be it structured or unstructured, online or offline in flat files, combines all this data in a meaningful way, uncovering patterns and trends, and be able to convey it to the business in the nicest possible way through either reporting systems or presentations. The role of a data analyst is limited to extracting relevant data and generating information out of it, leaving the inference and decision making part to the business analysts and top executives.
In this article let us look at:
The data analyst often is expected to study the data ecosystem and make recommendations about the data available for analysis, methods that can be improved to extract more meaningful data, bettering ways of data extraction, and the sources of data made available for analysis. Typical data analyst roles and responsibilities include the below among others,
The domains that a data analyst is expected to be well versed in are
Database Systems, Data extraction methods like SQL, NoSQL, flat file systems, programming languages, reporting tools, presentation tools.
An entry-level data analyst resume should be able to highlight Education in the field of computer science, mathematics, or statistics.
Academic projects – the roles specific to data analyst responsibilities that the candidate has taken up during his or her academic projects.
Online and offline courses that are specifically targeted at data domains like Data extraction- think SQL, Reporting tools-think Excel, Tableau among others.
Here is the sample entry level data analyst resume that can be used as guidance.
An experienced candidate would need to highlight two aspects of his/her data analyst resume,
A well-rounded data analyst resume sample for an experienced candidate is shown below. This may be used as guidance for preparing your own resumes.
A cover letter is the first thing that an employer will see on a resume. As they say, first impressions are lasting impressions, a cover letter makes a lasting impression, at least from an interview perspective, and will guide the direction of an interview. If the cover letter is brief with just the right amount of details, you will be interviewed most likely on your strengths than weaknesses.
Typically a cover letter gives a brief idea about the candidate’s career and special projects worth mentioning to the employer upfront. Let the cover letter be short and crisp enough for the employer to sift through.
The worst thing you could do is not know the content and format of your resume when going for an interview. Know each and every detail that goes into your resume before getting to the interview. Having prepared your resume well and knowing it well enough gives you that confidence you need during the interview.
As mentioned before a data analyst should have dabbled in several domains. We shall look into specific skills in each of those domains for a better understanding.
In today’s date, there are several database platforms available in the market, but they all are based on a few underlying technologies.
Some are Relational Database systems, others are Non-relational, and some Object-Oriented databases among others. So gaining knowledge and expertise in any one of these database systems and having enough knowledge about the other systems is a desirable skill.
The skill to extract data efficiently from the underlying databases or data warehouses is an important skill. SQL or Structured Query Language and No SQL scripts in databases like MongoDB. Many businesses judge the knowledge of the candidate in this field basis his or her knowledge of this aspect, be it SQL or No SQL.
Many a time it becomes imperative to use programming skills combining with data available to make an ad hoc custom solution as part of a reporting process. There are many Statistical programming languages like R and other general-purpose languages like Python which are well suited for the data analysis domain. These programming languages have several data-oriented packages that work efficiently with already extracted data or data to be extracted using embedded SQL scripts.
Reporting is the infrastructure that the business depends on to disseminate custom performance metrics to all groups within the organization in a more efficient and in near real-time. Knowledge in this domain is essential in ensuring that the work done by data analyst reaches the right audience at the right time.
Without adequate presentation skills, the knowledge you possess will be of little value. You should know how to tell your story, once it is complete.
Hope you crack your next Data Analyst interview with the given background and make it good in the data world.
To solidify Data Analysis & Management concepts, you should check out our Integrated Program In Business Analytics, in collaboration with IIM Indore. This 10-month online live program is easy to understand and designed by highly experienced experts to help learners become Future Leaders and transition into leadership roles.