Who is a Data Analyst?
A Data Analyst is a qualified professional responsible for acquiring data from different sources, cleaning and organizing it as well as conducting analysis on it. They happen to sift through data in order to identify patterns and trends, thus converting valuable business information into actionable insights. They make use of different Data Manipulation techniques in order to interpret complex datasets. In this capacity, they should be proficient in deriving meaning from numeric data, have a strong grip over programming languages, as well as be adept in the fundamentals of data handling. They generally operate on structured data for resolving quantifiable business problems.
Who is a Data Scientist?
Data Scientists generally hold senior positions and are possessors of advanced degrees. They utilize more advanced data techniques and strategies like neural networks, clustering, decision trees, and so on; for not only interpreting and analyzing data but also for making predictions about the future. They are highly proficient in Coding, Statistics, Mathematical Modeling as well as Machine Learning. Skilled with advanced programming, they are capable of creating new processes for Data Modeling.
Data Analyst vs. Data Scientist: Similarities
The topic of Data Scientist vs. Data Analyst is not necessarily an elaboration of the differences between the two positions alone. A proper analysis of the two positions will be incomplete without looking at the issue of Data Analyst vs. Data Scientist in terms of the similarities between the two professionals.
Both are responsible for dealing with Data in the accomplishment of business goals. Thus, they are often found to be working in the same business units.
Both are required to possess excellent written and verbal communication skills as they are responsible for conveying their findings to business leaders.
Both require expertise in traditional statistics.
Both the professions have garnered exceptional popularity in the public eye, especially with the intensification of the wave of the Data Boom.
Data Scientist vs. Analyst: Roles and Responsibilities
In this section, we shall look at the issue of Data Analyst vs. Data Scientist, in terms of what the two professionals are expected to do in their professional capacity.
Data Analyst
- Collecting Data from all possible Sources (Primary as well as Secondary)
- Identifying the Needs of the organization in liaison with the firm leaders
- Data Cleaning and Data Organization
- Writes SQL queries in order to derive Answers to Business Questions
- Work with customer-centric algorithm models
- Detect Data Quality Issues
- Conducting Analysis of Datasets in order to identify Trends and Patterns which could be converted into actionable Insights
- Applying Retrospective Analysis, Statistical Analysis, A/B Tests
- Designing and Creating Data Reports using different Reporting Tools
Data Scientist
- Acquiring Data, Performing Data Cleansing, and Processing Raw Data
- Making use of diverse tools like Python, Impala, Tableau, Excel, Hive, Hadoop, and others, in order to develop and test new algorithms
- Want to know more about Tableau, read our blog on “What is Tableau?: Learn from the Basics”
- Designing Machine Learning Algorithms and Predictive Models for Mining Big Datasets
- Correlating disparate Datasets as well as trying to look for Patterns and Trends in Data
- Identifying new Business Questions that can add Value
- Developing Custom Data Algorithms and Models as well as processes for analyzing Data Accuracy
- Develop Test Model Quality and A/B Testing Framework
- Generating Reports, Dashboards, and building Data Visualization Tools
Conclusion
The profession of a Data Scientist was branded as the ‘sexiest job of the 21st century” by the Harvard Business Review. Given the overwhelming increase in the importance of jobs related to the domain of data and information; Data Analysts, Data Scientists as well as Data Engineers have come to occupy esteemed positions within the job market. The question of Data Analyst vs. Data Scientist is not necessarily that one of one is better than the other. Rather the issue of Data Scientist vs. Data Analyst is simply an investigation into the technical differences between the two job designations.
The pursuit of jobs within the domain of Data Analytics or Data Science has come to be regarded as a wise career choice. They not only ensure handsome remuneration packages but also guarantee substantial opportunities for growth and diversification. We, at Syntax Technologies, provide you with an unmatched opportunity for developing expertise in line with the demands of the field of Data Analytics. Enroll now for our Data Analytics and Business Intelligence course.
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