Exploring Data Analyst Roles
Introduction
For last 5 Years I have updated my profile as a Big Data Analyst. Even when I had doubts about my exact role if I am working as a Data Specialist or really an Analyst, I got confused. In traditional sense I understood Data Analyst is someone whose job involves analyzing data and getting meaningful inferences from the data and presenting it in a usable format.
While depending on the job role the requirement and the tools used and the specific skill set may differ. But the core skill of analytical thinking and ability to making sense of the Data I feel is one of the most important skill that comes with a Data Analyst role. Today I will explore various aspects of being a Data Analyst how one can prepare to be a one and what points one has to take care when one searches for such a role.
Scope of a Data Analyst
A Data Analyst goes through the raw data in various formats and provide reports and visualizations to explain what insights the data is hiding. When somebody helps people from across the company understand specific queries with charts or usable representation, they are filling the data analyst role. He or she can work across a broad range of areas, including:
- business intelligence
- data assurance
- data quality
- finance
- higher education
- marketing
- sales
The typical data analysis process is composed of the following steps which a Data Analyst has to do on a day to day basis and may define the scope of his profile:
- The statement of problem
- Obtain your data
- Clean the data
- Normalize the data
- Transform the data
- Exploratory statistics
- Exploratory visualization
- Predictive modeling (Optional)
- Validate your model/inference
- Visualize and interpret your results
- Deploy your solution / Share findings via reports or presentations
If go back to my experience as a Data Analyst, I would say 80% of my time was spent on obtaining & cleaning data. In some ways I had developed advanced skills in Web Scraping and automated data collection. But the most painful part was the Data that came from Business users. To be honest depending on the tools you use to analyze and present the data, most of your time will be spent just on cleaning, transforming and loading the Data.
But in the 20% of the times I also spent in analyzing and making useful inferences on the Data. This not only enabled me in providing useful insights to the users but also helped in introducing new processes and optimizations that will bring value to the clients.
The scope of a Data Analyst varies depending on the Business needs, the type and source of Data. To analyze and present the outcome one has to be mindful of what the stakeholders want and what granularity of the outcome that is expected from the role.
Role of a Data Analyst
Depending upon their Level of Expertise, Data Analysts may have the following Roles :
- Determine Organizational Goals by understanding the Business requirements from IT and Business needs
- Data Analysts have to often mine or collect data. Getting data from the company database or extracting it from external sources to do any sort of research is one of the major roles of any Data Analyst.
- Data Analysts must start with a thorough data cleansing process. The good analysis rests on clean data–it’s as simple as that. Cleaning involves removing data that may distort your analysis or standardizing your data into a single format.
- While Analyzing the data, Data Analyst follow the process of evaluating data using analytical and logical reasoning to examine each component of the data provided. One uses statistical tools to analyze and interpret the data. There are various tools and programming languages used in the analysis.
- Data analyst spend a significant part of time on finding trends, correlations, and patterns in the complicated datasets. Trends are also important. Data Analysts look for both short-term and long-term trends. It helps you understand how your business has performed and predict where current business operations and practices will take you. It will give you ideas about how you might change things to move your business in the right direction.
- Being able to tell a compelling story with data is crucial to getting your point across and keeping your audience engaged. For this reason, data visualization can have a make-or-break effect when it comes to the impact of your data. Analysts use eye-catching, high-quality charts and graphs to present their findings in a clear and concise way.
- Data Analysts have to ensure that the storage, availability, and coherence of electronically stored data meet an organization’s needs. Data Analyst needs to have technical expertise regarding data models, database design development to make the best use of it.
As a Data Analyst I usually connected to enterprise wide Data Warehouse and Data Marts to extract their Meta Data and also got Business Terminology to form a enterprise wide Business Glossary and employed verity of Data cleaning , extraction and mining techniques to make the data usable. As part of my clients Data Governance initiative another key part of my role was Data enrichment and building Data Lineage for enterprise wise Data. End of the Data the work I had put in helped to build a robust enterprise wide Information Catalog for the client and that evolved with my changing roles and responsibilities in the organization.
Responsibilities of a Data Analyst
The responsibilities of a data analyst vary depending on the industry, but all require analyzing and interpreting data.
At their core, most include:
- Develop records management processes and policies
- Conduct consumer data research and analytics
- Work with customer-centric algorithm models and tailor them to each customer as required
- Extract actionable insights from large databases
- Perform recurring and ad-hoc quantitative analysis to support day-to-day decision making
- Create data dashboards, graphs and visualizations
- Support reporting and analytics, such as KPIs, financial reports, and creating and improving dashboards and develop and support reporting processes
- Prepare reports for internal and external audiences using business analytics reporting tools
- Help translate data into visualizations, metrics, and goals
- Mine and analyse large datasets, draw valid inferences and present them successfully to management using a reporting tool
- Write SQL queries to extract data from the data warehouse
- Identify areas to increase efficiency and automation of processes
- Set up and maintain automated data processes
- Identify, evaluate and implement external services and tools to support data validation and cleansing
- Monitor and audit data quality
- Liaise with internal and external clients to fully understand data content
- Gather, understand and document detailed business requirements using appropriate tools and techniques
- Design and carry out surveys and analyse survey data
- Manipulate, analyse and interpret complex data sets relating to the employer’s business
- Provide sector and competitor benchmarking
Despite what the job profile may demand, the real role of Data Analyst that you may do greatly depends on the environment and the business realities as you start working. When I started out I primarily my scope was just limited to Metadata analysis but as time went by and as stakeholders became comfortable with me and started depending on me, my responsibilities increased from not only obtaining / cleaning and transforming data but also providing insights, developing technical solutions, programming and also deploying solutions and also providing new knowledge domains and suggesting features that can add value to their business process.
Hot Data Analytics Roles
Regardless of where you are on your data analytics career path, it probably seems daunting to consider all the skills you need to be recruiter-ready. Typically, data lovers come from three different backgrounds.
- Starting from zero
- Strong programming background
- Strong mathematical background
- Some with string domain experience
A recent study by PWC estimated that there will be 2.7 million job postings for data analyst and data science roles by 2020. The study goes on to say that candidates must be “T-shaped,” which means they must not only have the analytical and technical skills, but also “soft skills such as communication, creativity, and teamwork.”
Finding someone who has the ideal blend of right-brain and left-brain skills is not an easy task, which is one reason why data analysts are paid well. Data analysis jobs and responsibilities require diverse skills. Before you take the time to learn a new skillset, you’ll likely be curious about the earning potential of related positions.
Lots of employers are hiring for these positions, both remote and onsite, worldwide. Here are a few positions worth looking into:
- IT Systems Analyst — Systems analysts use and design systems to solve problems in information technology. Though not directly related to a Data Analyst role but in this role also sufficient amount of Domain Knowledge and a bit of Data Analysis skills comes into play.
- Healthcare Data Analyst — Healthcare Data Analysts work in medical billing organizations or in healthcare units where they gather, analyze and compile medical data. They evaluate healthcare information in order to develop new procedures leading to higher levels of patient care and efficiency. Essential qualifications for this job are analytical thinking, attention to details, medical terminology familiarity, communication, computer proficiency and research skills. Most candidates mention a Bachelor’s Degree in healthcare administration in their resumes.
- Operations Analysts — Operations Analysts work to develop and implement business practices to ensure optimal performance within a company. Specific analyst job descriptions vary by company, but generally these professionals are responsible for identifying procedural, technical and structural shortcomings, and creating plans to fix those shortcomings. Candidates for operations analyst positions should have an awareness of dynamic market needs, a background in production and commerce and a set of business skills to assist in their decision-making.The operations analyst is a key member of the operations team supporting data management, client reporting, trade processes, and problem resolution.
- Business Analyst — The job of a business analyst is less technically oriented, the business analysts do wonders in their jobs for the deep knowledge of the different business processes.They master the skill of linking data insights to actionable business insights and is able to use storytelling techniques to spread the message across the entire organization. Business Analyst has good understanding of business and technology both.
- Data Engineer — Data engineers often focus on larger datasets and are tasked with optimizing the infrastructure surrounding different data analytics processes. For example, a data engineer might focus on the process of capturing data to make an acquisition pipeline more efficient. They may also need to upgrade a database infrastructure for faster queries.
- Quantitative Analyst — A quantitative analyst is a professional who uses quantitative methods to help companies make business and financial decisions. Investment banks, asset managers, hedge funds, private equity firms, and insurance companies all employ quantitative analysts, or “quants,” to help them identify profitable investment opportunities and manage risk.A quantitative analyst is another highly sought-after professional, especially in financial firms. Quantitative analysts use data analytics to seek out potential financial investment opportunities or risk management problems.
- Meta Data Analyst — Meta Data Analyst should have experience working with metadata from the perspective the end-user as well as a foundation in information organization and access. The roles & responsibilities involves selecting pre-defined metadata and includes eliciting information on such topics as sharing constraints, terms, use, and coverage.
Data collection of digital assets and work-product metadata through interviews and meetings with subject matter experts and recording the metadata in an automated tool. Liaise with SME and identification of gaps in controlled vocabularies and defined taxonomy. Work with taxonomist to iterate taxonomies and controlled vocabularies. This was the role that I primarily worked on in my previous organization and when I started out I was never aware the importance and the value of the role. But as my experience grew, I also valued the importance of the role and the opportunity to understand the business and the technology landscape that comes with it. - Master Data Analyst — Ensure master data integrity in key systems as well as maintaining the processes to the data quality.Ensures quality of master data in key systems, as well as development and documentation of processes with other functional data owners to support ongoing maintenance and data integrity. Assists in the application and implementation procedures of data standards and guidelines on data ownership, coding structures, and data replication to ensure access to and integrity of data sets. Conducts data cleaning to rid the system of old, unused data, or duplicate data for better management and quicker access.
- Data Analytics Consultant — Like many of these positions, the primary role of an analytics consultant is to deliver insights to a company to help their business. While an analytics consultant may specialize in any particular industry or area of research, the difference between a consultant and an in-house data scientist or data analyst is that a consultant may work for different companies in a shorter period of time.
- Data and Analytics Manager — The one who manages data and analytics is the driver of the team. He/she gives direction to the data science team and makes sure the right priorities are set. The person combines strong technical skills in a diverse set of technologies like SAS, R, SQL, Excel, Python etc with the social and leadership skills required to manage a team.
- The Data Architect — The importance of data architect jobs is also increasing with the rise of big data. The person in this role creates the blueprints for data management systems to centralize, integrate, maintain, and protect the data sources.Data Analyst and Database Designer makes the role of a Data Architect. They integrate data from different unrelated data sources to help find relevant information.
- Statistician — The job of a statistician is to represent the data science field for getting useful insights from data. Having a logical and stats oriented mindset, and a strong background in statistical methodologies, and theories, a statistician harvests the data and turns it into knowledge and information. If you are going for this job profile, make sure you can handle all sorts of data. The quantitative background helps the modern statisticians to quickly master new technologies and use these to boost their intellectual capabilities.
Skills Needed for a Data Analyst
From the above Job profiles and roles and responsibilities its clear that a Data Analyst would need a diverse set of Skill set and much of it may be developed on the Job. From personal experience as a minimum good communication and soft skills, knowledge of Excel, Databases, basic statistical analysis and knowledge of business domain will go a long way in mastering the needs of the Data Analyst role. Additionally you can use the below reference though not exhaustive to develop the skills required to be a Data Analyst:
- Degree in mathematics, statistics, or business, with an analytics focus
- Excellent numerical and analytical skills
- Knowledge of data analysis tools — you don’t need to know all of them at entry level, but you should show advanced skills in Excel and the use of at least one relational database
- Familiarity with other relational databases (e.g. MS Access)
- Knowledge of data modelling, data cleansing, and data enrichment techniques
- Experience working with languages such as SQL, R, Python
- A solid understanding of data mining techniques, emerging technologies (Hadoop, MapReduce, Spark, large-scale data frameworks, machine learning, neural networks) and a proactive approach, with an ability to manage multiple priorities simultaneously
- Google Analytics, SEO, keyword analysis and web analytics aptitude, for marketing analyst roles
- A strong combination of analytical skills, intellectual curiosity, and reporting acumen
- The capacity to develop and document procedures and workflows
- The ability to carry out data quality control, validation and linkage
- An understanding of data protection issues
- For some roles, an awareness and knowledge of industry-specific databases and data sets (particularly in higher education)
- Experience of statistical methodologies and data analysis techniques
- The ability to produce clear graphical representations and data visualisations.
- Familiarity with agile development methodology
- Exceptional facility with Excel and Office
- Strong written and verbal communication skills
Depending on your exact role, you’re likely to need skills in some of the following technical skills:
- VBA, MS Access and SQL Server
- APIs, Micro Services & Cloud (AWS, Azure)
- XML, JSON, CSV file formats
- Business Intelligence and analytics platforms — Tableau, QlikView, Crystal Reports, D3, Alteryx
- Statistical programs — SPSS, SAS, RapidMiner
How to Prepare to Be a Data Analyst
Taking the initiative to learn data analysis skills and programs in addition to your degree will help you develop your skills and help set you apart. You can also learn a lot of desirable data analysis skills through short courses offered at universities and specialist data schools, such as:
Personally I have been taking classes from Cognitive Classes, Udemy and Coursera and they are really good. And I would recommend these as the best source to start.
Additionally another great way of learning is via sharing. Start with small experiments, be part of hackathons. Share your knowledge via Blogs, github and even be part of communities and open source initiatives which will not only help you gain valuable knowledge but also help to gain valuable experience which is not always possible on the job. Two of best examples that I can give from my experience are two of my blogs which helped me learn lot of things as I did experimentation and knowledge sharing.
Data Analyst Salaries
Again this is a very subjective point and depending the career level you are in and depending on the skill set and the roles and responsibilities these figures may change. I will share the below info graphics to give you a better picture.
As you grow in your career and specialize in a specific area of Data Analytics, and depending on your domain the opportunities and the salary growth opportunities will differ. But always having strong analytical and technical skill sets with a deeper domain/business knowledge helps to grow further in your career.
Finally
Data analysis is a fast-growing field and skilled analysts are in high demand across all sectors. According to the World Economic Forum, data analysts are expected to be in the top ten jobs in demand in 2020.
This demand for experienced analysts is only likely to grow in years to come, This is coupled with the fact that data specialists are required across multiple industries and domain types, including healthcare, manufacturing, education, media, retail and even real estate. Because of this, advancing in the role should be a fairly quick process.
A data analyst typically has a more mathematical or statistical mindset, while a business analyst has more of a business mindset. Data analysts tend to spend more time collecting and sifting through data, while business analysts tend to have more interaction with other team members. Starting with basic data analytical skills you can hone your data modeling and coding skills to excel in job as a data analyst.
For me who has spent almost 4 Years in a Data Analyst role, I still feel there is great opportunity to grow and with more focus on Data Visualization, Story telling, Machine Learning, Predictive Analytics and Deep Learning. All of this will only make more sense when we focus on credible business outcome and help to add value through with deeper domain knowledge and develop necessary soft skills to build successful relationships in business processes and teams that we are part of.
Reference
During my research I found the below links very useful, much of my material for the blog is credited to the below articles & blogs. Hope these may help you as well
