Data Analysis vs. Data Science
Published: 2020-07-22 21:31:14

Within this day and age of technological advancements, everything revolves around this perplexing composition of data. Data is usually undermined by the vast majority, because people often fail to acknowledge that it essentially entails future projections and allows stability within a variety of sectors. Data can be drawn from anything and everything we fulfill in our everyday lives, whether its YouTube running the videos you have watched through an algorithm to yield recommended videos in your explore page or simply how we interact with any given website. These daily actions that we execute are constantly being recorded and analyzed to project and predict future outcomes. Whether we acknowledge it or not, data possesses a pivotal role within all of our lives and helps make certain tasks seamless. 

A key factor to a successful company is their focus towards how they consider and account data to contribute towards making executive decisions for the betterment of their company. This implicates that a company’s prosperity is contingent upon their data team and alludes to the idea of why the data sector is so prominent and in demand. There are various positions within this ambiguous data umbrella, but what does each position entail in terms of responsibilities and skillsets that are required? 	

Data analysts are one of the most notable positions within the data world, their responsibilities include but are not limited to retrieving, gathering, and organizing data in order to make meaningful decisions. They provide technical expertise to ensure accuracy of any given data and then they transform this data into a concise manner in order for it to presented to their peers. A primary reason as to why this position is so in demand and versatile is due to the fact that all sectors of businesses are in desperate need of analysts who can help their company succeed and attain longevity relative to their competitors. Whether you’re a Fortune 500 company or merely a small niche tech start-up, you will need analysts to provide their expertise on the general direction of the company.  
	
In order to understand what a data analyst truly does; it would be necessary to delve into their responsibilities fulfilling that position. The most notable responsibility of a data analyst is to possess the skill of being able to compile and produce reports. These specific reports draw data from a larger cohort and decompose it into a concise amount of information that is presented in a clean and digestible manner. These reports provide valuable insight about potential trends or anything uncanny that may have transpired and allows higher-ups to decide where the company may or may not need to improve. Another skillset a data analyst should possess is to be able to discern patterns that occur gradually over time. In order to produce a compelling report, it would be necessary to figure out the occurrence of these said patterns in order to prevent or to encourage any given outcome. An analyst should be versatile in using statistical tools to interpret data sets, as this will help produce valuable information in regard to predictive analytics. For example, taking previous reports into consideration as well as one’s experience, one can eventually anticipate a given outcome, if the occurrence has happened more than once. 

Another position within the data sector that is just as prevalent is the Data Scientist. The roles of this position are quite ambiguous in the sense that some responsibilities of this position overlap with the analyst. This is a primary reason as to why there’s a gray line in between the two, mainly because it’s quite difficult to pinpoint and distinguish which position is in charge of what. However, the most important distinction between the two are that data scientists are in charge of anticipating the future based on previous patterns, whereas an analyst merely curate’s meaningful insight from data. 

It would be quite difficult to summarize into a brief understanding of what a data science does mainly because the job entails a variety of things contingent on your position. However, a compelling description would state that Data scientists develop predictive and prescriptive algorithms as a result of interacting with a clean data set. To simplify this a little more, they’re in charge of gathering and organizing the data in order to solve process and strategy problems to accommodate to businesses and enterprises. They explore data with the necessary tools to applicate meaning to a large dataset. This is most effectively done by the use of data visualization, in order to convey and translate their findings into an approachable manner for their peers. Data visualization allows one to compile a series of complex data in to a much more appealing and understanding form. 

Aside from entering this field due to a passion or love for statistical math and mental application, jobs in the data sector are being labeled as “The Sexiest Jobs of the 21st Century.” These positions have substantially gained traction from individuals as the job outlook is on a constant gradual increase. According to the Flat Iron School, Data science is one of the fastest growing sectors amongst the tech industries and is estimated to have a 650% growth in positions since 2012.