What is the Difference between Data Science and Big Data

As we are moving into the digital era, technologies such as data science & big data are most commonly used. They have become the buzzword as well as the most significant assets in the world of IT. Often people tend to use these terms interchangeably, but the fact is that there are major differences among these concepts.

Since both the fields are interlinked & quite confusing, I have listed the major differences among them in a simple manner.

• Meaning

Data Science is a multidisciplinary field which comprises mathematics, programming, statistics and deals with both structured & unstructured data. It is a branch of study that involves everything associated with data cleansing, preparation & analysis.

Big data refers to massive volumes of complex sets of data that cannot be processed & analyzed through conventional technologies. The concept of big data is associated with 5 V’s i.e., velocity, variety, volume, variability & veracity of data which needs advanced information processing systems to derive meaningful insights.

• Applications

Data Science is applied in digital advertisements, internet search, web development, e-commerce, telecom, finance, etc.

Big data has widespread applications which include transportation, government, retail, healthcare, financial sector & a lot more.

• Scope

Data Science has a much wider scope than big data. It includes a variety of operations which is generally done on big data.

Big Data has a narrower scope than data science. It is all about storing those massive chunks of data.

• Roles & responsibilities

Data Science professionals deal with both structured & unstructured data & perform exploratory analysis to derive meaningful insights from them. They concentrate on recognizing hidden patterns, market trends & unknown correlations.

Big data analytics deals with vast amounts of data collected through several sources. These professionals come up with the solutions for big data problems & describe the ways in which they can be achieved utilizing big data technologies.

• Skills required

Data scientist requires knowledge of programming languages, data visualization tools, data mining along with a solid understanding of mathematics & statistics.

Big data professionals require knowledge of Hadoop, Spark, SQL. They also require a good understanding of programming languages & knowledge of NoSQL databases.

• Salary trends

Data Scientist professionals earn an average salary package of US $105,750- US $ 180,250.

Big Data Specialists, on the other hand, earn an average salary package of US $130,000- US $ 222,000.

I hope the above points were enough to clarify the difference between Data Science & Big Data.