Data Science Roadmap
Data has changed the face of our world over the last ten years. The numerous emails, text messages we share, YouTube videos we watch are part of the nearly 2.5 quintillion bytes of data generated daily across the world. Businesses, both large and small, deal with massive data volumes, and a lot depends on their ability to glean meaningful insights from them. A data analyst does precisely that. They interpret statistical data and turn it into useful information that businesses and organizations can use for critical decision-making.
Organizations in all sectors are increasingly depending on data to make critical business decisions like which products to make, which markets to enter, what investments to make, or which customers to target. They are also using data to identify weak areas in the business that need to be addressed.
As a result, data analysis has become one of the highest in-demand jobs worldwide, and data analysts are sought after by the world’s biggest organizations. Data analyst salary and perks only reflect the demand of this job role which is likely to keep growing in leaps and bounds.
So if you have the skills required to become a data analyst, you would be remiss not to take advantage of this scenario. In this article on ‘data analyst job descpription’ let us take a look at all the aspects related to this job role and finally discuss a data analyst job description in detail.
What Is Data Analysis?
The process of cleaning, analysing, interpreting, and displaying data using different approaches and business intelligence tools is known as data analysis. Data analysis tools assist you in uncovering key insights that lead to better informed and successful decision-making. It is concerned with the transformation of raw data into meaningful statistics, information, and explanations.
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What Does a Data Analyst Do?
A data analyst analyses data sets to find ways to solve problems relating to a business’s customers. A data analyst also communicates this information to management and other stakeholders. The employment of these individuals encompasses many different industries such as business, finance, criminal justice, science, medicine, and government.
The role of a data analyst can be defined as someone who has the knowledge and skills to turn raw data into information and insight, which can be used to make business decisions.
Types of Data Analysts
Medical and Health Care Analyst
As the name implies, medical and healthcare data analysts use data from a number of sources to assist improve healthcare outcomes. They typically concentrate on the business side of medicine, increasing patient care or simplifying operations.
Market Research Analyst
Market research analysts collect and evaluate consumer and competitor data. Market research analysts investigate market circumstances in order to assess future sales of a product or service. They assist businesses in determining what items customers desire, who will buy them, and at what price.
Business Analyst
Data is used by business analysts to create business insights and advocate improvements in corporations and other organisations. Business analysts may detect problems in almost any aspect of a business, including IT processes, organisational structures, and employee development. As companies are constantly striving to improve their overall efficiency and save expenses, business analytics is gradually becoming an essential component of their operations.
Business Intelligence Analyst
A business intelligence analyst (BI analyst) analyses data and other information to assist firms in making effective business choices. They may collect, clean, and analyse data such as a company’s revenue, sales, market intelligence, or consumer engagement indicators. BI analysts may also be required to create tools and data models to aid in the visualisation or monitoring of data.
Operations Research Analyst
Operations research analysts are high-level issue solvers that employ sophisticated problem-solving approaches such as optimization, data mining, statistical analysis, and mathematical modelling to provide solutions that help firms and organizations function more efficiently and cost-effectively.
Intelligence Analyst
Analysts of intelligence examine information and data in order to identify and mitigate security concerns. Internal and external statistics, databases, and field reports are examples of information sources. To synthesise information and generate action plans, analysts must have good research, comprehension, and analytical abilities.
Data Analyst Job Description: Roles and Responsibilities
A data analyst is responsible for organizing data related to sales numbers, market research, logistics, linguistics, or other behaviours. They utilize technical expertise to ensure data is accurate and high-quality. Data is then analyzed, designed, and presented in a way that assists individuals, businesses, and organizations make better decisions.
- Using automated tools to extract data from primary and secondary sources
- Removing corrupted data and fixing coding errors and related problems
- Developing and maintaining databases, data systems – reorganizing data in a readable format
- Performing analysis to assess quality and meaning of data
- Filter Data by reviewing reports and performance indicators to identify and correct code problems
- Using statistical tools to identify, analyze, and interpret patterns and trends in complex data sets that could be helpful for the diagnosis and prediction
- Assigning numerical value to essential business functions so that business performance can be assessed and compared over periods of time.
- Analyzing local, national, and global trends that impact both the organization and the industry
- Preparing reports for the management stating trends, patterns, and predictions using relevant data
- Working with programmers, engineers, and management heads to identify process improvement opportunities, propose system modifications, and devise data governance strategies.
- Preparing final analysis reports for the stakeholders to understand the data-analysis steps, enabling them to take important decisions based on various facts and trends.
Another integral element of data analyst job description is EDA or Exploratory Data Analysis Project. In such data analyst projects, the analyst needs to scrutinize data to recognize and identify patterns. The next thing data analysts do is use data modeling techniques to summarize the overall features of data analysis.
Data Analyst Skills Required
As a data analyst, you should possess the following eight skills:
- Cleansing and preparing data
- Analyzing and exploring data
- Expertise in statistics
- Analyzing and visualizing data
- Reports and dashboards
- Communication and writing
- Expertise in the domain
- Solution-oriented
Now that you know the data analyst job description, let us look at the skills required to become one. A successful data analyst needs to have a combination of technical as well leadership skills. A background in mathematics, statistics, computer science, information management, or economics can serve as a solid foundation to build your career as a data analyst.
Key Skills for a Data Analyst
- Strong mathematical skills to help collect, measure, organize and analyze data
- Knowledge of programming languages like SQL, Oracle, R, MATLAB, and Python
- Technical proficiency regarding database design development, data models, techniques for data mining, and segmentation.
- Experience in handling reporting packages like Business Objects, programming (Javascript, XML, or ETL frameworks), databases
- Proficiency in statistics and statistical packages like Excel, SPSS, SAS to be used for data set analyzing
- Adept at using data processing platforms like Hadoop and Apache Spark
- Knowledge of data visualization software like Tableau, Qlik
- Knowledge of how to create and apply the most accurate algorithms to datasets in order to find solutions
- Problem-solving skills
- Accuracy and attention to detail
- Adept at queries, writing reports, and making presentations
- Team-working skills
- Verbal and Written communication skills
- Proven working experience in data analysis
What Tools Do Data Analysts Use?
SQL
SQL is widely used for data analysis in major corporations, and it is regarded as one of the most important tools for analysts. SQL is also used in software development by software engineers. SQL is a computer language that was designed to manage data from relational databases. It is a simple tool to learn and may be used for complicated, difficult data analyses. It is a popular option among data analysts since the code is simple to read and comprehend, and it can be used to edit and update data. Furthermore, it allows you to compile data in a way similar to Excel, but over enormous datasets and across numerous tables at once.
Microsoft Excel
Excel, a data analysis industry standard, is the most important tool to master as a data analyst. It is a simple application to learn, and data analysts should be adept in all parts of Excel, from formula to pivot tables. Any spreadsheet application will work, although Microsoft Excel is the most popular.
SPSS and VBA
Analysts frequently require a statistical analysis programme such as SPSS in addition to the instruments listed above. SPSS is an excellent choice for freshly certified analysts (more on SPSS below). VBA – Visual Basic for Applications – may be required by more experienced data analysts. It is a programming language built exclusively for Excel and is frequently used in financial analysis. It is also Word and PowerPoint compatible. Matlab is another excellent tool for creating algorithms, building models, and analysing data.
Jupyter Notebooks
Project Jupyter is a one-of-a-kind service dedicated to the development of open-source software, open standards, and interactive computing services. It is compatible with a wide range of programming languages. As an open-source online tool, Jupyter Notebook allows you to create and share documents that may contain live code, equations, graphics, and narrative prose. The notebook may be used for a variety of purposes, including data cleansing and transformation, machine learning, and more.
R
The open-source programming language R, which is compatible with all platforms (Windows, Mac OS, and Linux), is another important and widely used tool in data analytics. It is widely used by statisticians for statistical modelling because it provides a wide range of statistical and graphical options, and it is frequently used to undertake data wrangling. It allows the data analysts to create data visualisations such as plots and graphs and is accessible in a variety of libraries such as Plotly. It’s employed in banking and sales, as well as several scientific sectors including medicine and technology. To use this data analysis tool, you must have a basic understanding of statistics and programming in general.
Tableau
Tableau is another application that is often used by data scientists. It is widely utilised since data can be evaluated fast with it. Dashboards and spreadsheets are also created for visualisations. Tableau enables the creation of dashboards that deliver actionable information and propel a business ahead. When configured with the appropriate underlying operating system and hardware, Tableau products always run in virtualized environments.
SAS
SAS (Statistical Analysis System) is a well-known commercial suite of business intelligence and data analytics tools. The SAS Institute created it in the 1960s, and it has evolved since then. Its primary applications now are client profiling, reporting, data mining, and predictive modelling. Designed for the business market, the software is often more robust, adaptable, and user-friendly for large enterprises. This is due to the fact that they have differing amounts of in-house programming competence.
Microsoft Power BI
Microsoft Power BI is a relative newcomer to the market of data analytics tools, having been around for less than a decade. It originated as an Excel plug-in before being updated as a full suite of corporate data analysis tools in the early 2010s. Power BI helps users to quickly and easily generate interactive visual reports and dashboards. Its key selling point is its excellent data connectivity—it works well with Excel (as one would expect from a Microsoft product), but also with text files, SQL servers, and cloud sources such as Google and Facebook analytics.
Data Analyst Qualifications: What Does it Take
After data analyst job description and skills, let us learn more about the qualifications of a data analyst. You need more than technical expertise to excel in a career in data analytics. A bachelor’s degree in a field that emphasizes on statistical and analytical skills is desired. Students from mathematics, statistics, computer science, or economics background usually have an edge in the data analyst career path. However, a postgraduate course in data analytics like Data Analytics Bootcamp can make you an industry-ready professional.
You would also need soft data analyst skills like:
- excellent communication and presentation skills
- ability for critical thinking
- creativity
- having a systematic and logical approach to problem-solving
- team working skills
Data Analyst Salary: How Much Does a Data Analyst Make?
Does the data analyst job description excite you enough? If not let us look at some salary figures of this in-demand job role. However, note that, the data analyst salary depends on a number of factors like educational qualification, location, relevant experience, and skills set.
The average annual salary of an experienced data analyst can range from approximately $60,000 to $140,000. Financial and technology firms tend to offer higher pay-package than average.
The cross-market average data analyst salary is approximately $73,528
Data analysts typically move on to higher positions like senior data analysts, data scientists, data analytics managers, business analysts, etc. Higher responsibilities come with a substantial pay rise as well. It is estimated that the average annual salary of data scientists starts at around $95,000, while that of analytical managers begins at approximately $106,000.
Watch the video below that will help you have an understanding of the various responsibilities, skills required, and the salary structure of top Data Analytics job roles.
Top Companies Hiring Data Analysts
If you are looking for a data analyst job, you can choose from more than 86 thousand open jobs worldwide. Shocking, isn’t it? This is mainly because nearly all industries benefit from data analysis. Today, the data analyst job description is branching off into various specializations like finance, healthcare, business, marketing, and e-commerce.
Presently, business intelligence companies have the highest number of job openings for data analysts in the US and Europe, followed by finance, sharing economy services, healthcare, and entertainment companies.
Some of the top global companies hiring data analysts include Amazon, Netflix, Google, Intuit, Facebook, Apple, CISCO Systems. Smaller companies include Focus KPI, Affinity Solutions, Norgate Technology, Financial giants like Paypal and Barclays are also hiring data analysts across various departments.
FAQs
1. What are the duties and responsibilities of a Data Analyst?
Data analysts are responsible for analyzing data using statistical techniques, implementing and maintaining databases, gathering data from primary and secondary sources, identifying, analyzing and interpreting trends from the data.
2. What makes a good Data Analyst?
A good Data Analyst is inquisitive, strategy-oriented and has the ability to think outside the box for innovative solutions. They should be able to operate in a systematic and scalable manner and have excellent communication skills.
3. Who does a Data Analyst work with?
Who a Data Analyst works with depends on the type of industry their work within. Data Analysts work in multiple industries including finance, business, science, government, medicine, etc.
4. Do you have examples of data analyst interview questions?
Data Analyst interview questions include questions such as What are the best methods for cleaning data?, Significance of Exploratory Data Analysis (EDA)?, Which are the technical tools that you have used for analysis and presentation purposes?, Explain descriptive, predictive, and prescriptive analytics, etc.
5. What does a Data Analyst do?
A Data Analyst is responsible for collecting, organizing, cleaning and identifying trends from raw data.
