Well, I don’t blame you, for the industry working definitions of these two job titles are pretty inadequate. Both disciplines (if I may call them such) have overlapping areas and are usually complementary. At the same time, the titles call for a mixed bag of different skill sets, qualifications and operational roles that set them apart.
While the analytics space has many job titles (Data Engineer, Business Analyst, Computer Scientist, Big Data Practitioner, Econometrician, Data Miner, etc.); a thumb rule for distinguishing a Data Analyst from a Data Scientist is the functional role within the data life cycle and the continuum of skills called for.
While the Data Analyst aggregates data for visualization and building organisational database; the Data Scientist extracts useful information from the data for predictive insights and facilitating business decisions.
So let us examine in detail what these titles are about.
Usually an entry level job, the Data Analyst is nevertheless core to the analytic workspace. He deals with data at every primary and aggregator level, linking business data with the reporting. While a Data Analyst maybe considered a junior title in a smaller company, he would occupy a senior and specialised position in a large organization.
The Data Analyst makes data usable for insights in real-time, often performing multiple roles of database administration, BI and data-on-demand.The job role spans the length and breadth of data, ranging from extraction of statistical information and building of the organisational RDBMS to presentation and visualization.
Is Data Scientist, a scientist who experiments with data for modelling or a data professional who administers data for further analysis? Well, we’d say, he is both!
A Data Scientist is a practitioner of Data Science – the study of applying machine learning, statistics, computer science or other scientific discipline – to interpret and extract knowledge from large amounts of data for predictive modelling. Although the formal training for a Data Scientist is similar to that of a Data Analyst (see below), what sets him apart is his business insight. He is expected to summarise data and systematically design forecasting models based on research, and validate the same for the decision making process.
When a Data Scientist works in equity – high frequency trading, predicting stock prices – he may be referred to as a Quant! Quaint as this title may sound, the title is associated with high grossing salaries.
There is no strict dictum about the qualifications or expertise requirement for a Data Scientist. Rather it is the nature of job role, the industry, the company policy and projects handled, that define the qualifications or skill sets required of the Data Scientist. As the volume of data increases, the ability to handle Big Data and proprietary software becomes a must-have.
Qualifications and Skills required
- Degree in statistics, mathematics or computer science
- Knowledge of databases, data warehousing and Business Intelligence
- Knowledge of all file types and importing them into the database
- Expertise in data storage, retrieval, application of ETL tools
- Knowledge of Excel, SQL, data modelling
- Knowledge of Hadoop and R based analytics
- Ability to analyse data in real-time
- Working knowledge of the business
- Communication savvy
- Degree in mathematics/ statistics /computer science with preference for a PhD; and/or proficiency in the above disciplines
- Knowledge of one or more programming languages with ability to code, firm grasp on relational and SQL/ MySQL database systems, distributed architectures, machine learning, data mining algorithms and data modelling techniques, operations research
- Knowledge of SAS, SPSS, Python and R
- Knowledge of Big Data, and ability to analyse large datasets
- Creative thinking and in-depth knowledge
- Business acumen and IT savvy
Data Analyst vs. Data Scientist
At the end of the day, it all boils down to jobs and salaries.
Here are some random examples of titles you can expect.
According to PayScale, the average pay for a Data Analyst is Rs 292,953 /year with highest paying skills associated with VBA, SAS, and SQL. “Most move on to other jobs if they have more than 10 years’ experience” is what it says. However, the average salary for a Data Scientist, logs more than double at Rs 680,337.
Many young professionals start their career with the title of Data Analyst and gradually evolve / migrate as show below.
Pinned from Payscale.com
If you are STILL wondering what this appellation is all about, have fun reading this thread!