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Data Science vs Data Analytics — How to decide which one is right for you?

Sankhyana Consultancy Services-Kenya

Data Driven Decision Science (Training/Consulting/Analytics)

发布日期: 2022年7月15日

Data Analytics and Data Science are the buzzwords of the year. For folks probing for long-term vocation potential, immensely colossal data and data science jobs have long been a safe bet. This trend is liable to perpetuate as AI and Machine Learning become highly integrated into our circadian lives and economy. Today, data is the incipient oil for businesses to accumulate critical insights and amend business performance to grow in the market. But who will glean insights? Who will process all the collated raw data? Everything is done either by a data analyst or a data scientist. These are the two most popular job roles in this area as companies across the world look to make the most out of data. Data Science and Data Analytics is a mishmash of terms which interweave and overlap with one another but are still quite different.

Affirmative, professionals(both abecedarians and transitioners), we have our auditory perceiver to the ground. Many of you getting commenced with a vocation in data analytics or data science are often confounded and unsure about which is the right vocation path for you. Well, the decision would depend on what your vocation goals are, as well as your skills and competencies. That verbalized, to spare you from any kind of mystification and provide you a crystal clear insight into these two innovative vocation paths, here we explore Data Analysis and Data Science. This article aims to avail you better understand the distinction between the two disciplines so that you can make a decision as to which vocation path would better suit your vocation aspirations.

Data Science vs Data Analytics — Understanding the Differences

Data Science vs Data Analytics — The Fundamental Goal

Data Analytics — Analyse and Mine Business Data

Data Science — Discover the right business questions and find answers.

Data analysis involves answering questions engendered for better business decision making. It utilizes subsisting information to unearth actionable data. Data analytics fixates on categorical areas with categorical goals. On the other hand, data science fixates on discovering incipient questions that you might not have realized needed answering to drive innovation. Unlike data analytics which involves checking a hypothesis, data science endeavors to build connections and shapes the questions to answer them for the future. If data science is an abode for all the methods and implements, data analytics is a minute room in that house. Data analytics is more concrete and concentrated than data science.

Data analytics focuses more on viewing the historical data in context while data science focuses more on machine learning and predictive modeling. Data science is a multi-disciplinary blend that involves algorithm development, data inference, and predictive modeling to solve analytically involute business quandaries. On the other hand, data analytics involves a few different branches of broader statistics and analysis.

Data Science vs Data Analytics — The Skills

Data Analytics — Erudition of Intermediate Statistics and excellent quandary-solving skills along with

Dexterity in Excel and SQL database to slice and dice data.

Experience working with BI implements like Power BI for reporting

Erudition of Stats implements like Python, R or SAS

To become a data analyst, one need not compulsorily hail from an engineering background but having vigorous skills in statistics, databases, modeling, and predictive analytics comes as an integrated advantage.

Data Science — Math, Advanced Statistics, Predictive Modelling, Machine Learning, Programming along with –