Comparison of Data Science vs Data Analytics and Big Data
What is Data?
Data can be a collection of facts or information that is organized in a particular way. It refers to information, figures, or facts that are stored on a computer.
Data can be structured or unstructured.
Structured Data
Structured data is consistent, well-defined and easy to store and access. Indexes can be used to search stored structured data.
Unstructured Data
Unstructured data can be inconsistent data that lacks any sequence, format or structure. When indexing is done on it, it is prone to multiple mistakes which makes it difficult to understand and operate unstructured data.
The amount of data generated in this digital age is staggering and is causing rapid changes in our lives. Since we have more unstructured data in real life, in the form video, audio and text, the storage problem is now solved.
Data procession is often associated with terms such as Data Science, Big Data, and Data Analytics. There has always been confusion among these terms.
This article will help you to clarify the similarities and differences between big data, data science and data analytics.
We will explain each one in the following format to keep things simple.
* Definition,,and Concepts
* Skillsets required
* Professional roles in their individual capacities
* Income, job scope, and career growth
* Applications
* Trends
* Economic Importance
Data Science, Big Data and Data Analysis
Definition,, and concepts
What is Data Science?
Data Science is data preparation, data cleansing and data analysis. It is a tool for extracting information and dealing with Big Data.
Data scientists collect the initial data sets from different disciplines, such as statistics and mathematics. Then they apply predictive analysis and sentiment analysis to help them understand the point better and then derive something. Finally, the useful information required is extracted from it.
Data scientists provide accurate predictions and changes to data by understanding it from a business perspective. This helps to prevent future losses for business people who are part of top data science programs.
What is Big Data?
According to Gartner, Big Data is high volume, high velocity and high variety information data that requires cost-effective information processing innovation forms that enable process automation, enhanced insight and decision making.
Big Data database refers to the enormous amount of data that is hard to process by traditional applicators.
Big Data processing begins with non-aggregated raw data that cannot be stored on a single computer. Big Data technology is used to run a business every day. Big Data systems analyze data and make better business decisions.
Big Data is simply a large volume of data that grows with time. It is so complex and enumerous that no data management tool can efficiently store or process it.
Big Data Applications
Combining big data with high-powered analytics can allow you to complete a business-related task like finding the root cause of failures, defects and issues in almost real time, calculation of all risk portfolios in minutes, detection and prevention of frauds before they have an effect on your organization, and the ability to generate coupons based upon customer buying habits at the point-of-sale.
What is Data Analytics?
Data Analytics is the process of determining the conclusion of information from its raw data. It involves the application of a mechanical process, or an algorithm, to derive insights. This could include going through multiple data sets and searching the relation between them.
Different industries use data analytics basics to verify and disagree on existing theories or models. Data analytics programs are focused on arriving at a conclusion based on what is already known.
What is Data Analytics? What is Big Data Analytics?
Data analytics is the process of performing advanced analytics on large and diverse data sets from many sources. It can be either structured, semi-structured or unstructured. The data can be of various sizes, up to terabytes or zettabytes.
Skills required in Data Science, Big Data, and Data Analytics
This section will allow you to compare your skills in data analysis