The term Big Data is used to describe the huge volumes of structured and unstructured data that is very difficult to process using the traditional methods. These large sets of data are analyzed computationally to discover certain patterns and trends. Big Data comprises of huge samples of data, enough to draw good conclusions and there is no minimum amount of it.

The concept of Big Data is new, and increasing amount of different types of data is being collected. With digitization, more and more information is moving online and it is readily available for analysts.

How to access Big Data?

Big Data is increasing with every passing minute and is available in a countless number of places on the web. Just one simple Google search brings out millions of results with large volumes of data. It can’t be righty judged how much data is available online. Here is how you can access and use the data:

  • Data Extraction:

    Data extraction is the process of gaining data. There are many ways to do it but it is generally done by making an API call to an organization’s web service.

  • Data Storage:

    Storage is a big problem when it comes to big data. A lot depends on the budget and expertise of the person responsible for setting up the storage. Technical skills and programming knowledge is important for this purpose. A good provider is someone who allows you a safe place to store your data.

  • Data Cleaning:

    Data is available in different sizes and may be unorganized. Therefore, before you store it, you need to run data cleaning in order to convert it into an acceptable

  • Data Mining:

    Data mining is the process of finding insights into the database. The purpose of it is to make predictions and decisions on the data that is currently available.

  • Data Analysis:

    After the data is collected, the next step is to do analysis and find any interesting trends or patterns. A good analyst is someone who can find something important in the ordinary or something no one else has

  • Data Visualisation:

    The visualization of data is deemed to be very important. It is a process of using all the previously done work and putting it in words that everyone can understand.

Important terms to know

  • Algorithm

An algorithm can be defined as a set of instructions or a mathematical formula that forms the base of a software used to analyze the data.

  • Hadoop

It is a collection of programs that allow the users to store, retrieve, and analyze the large sets of data.

  • Data Scientist

A data scientist is someone who has the expertise in deriving insights and analysis from the data.

  • Amazon Web Services (AWS)

AWS is the name given to the collection of cloud computing services that help the businesses to do large-scale computing operations without the requirement of any storage or processing power on-premise.

  • Cloud Computing

The term cloud computing is given to the process of running software on remote servers and not locally.

  • Internet of Things (IoT)

The IoT is a relatively new technology in which the objects like sensors collect, analyze, and transmit their own data without any manual input. In essence, the devices’ functioning is controlled over the internet.

  • Web Scraping

Web scraping is the process of automatic collection and structuring of data from websites.

  • Predictive Analysis

It is about predicting the future trends or events using the available data.

  • Structured and Unstructured Data

Data that is properly organized in the form of a table so that it relates to other table or chart is called structured data while all other unorganized data is called unstructured data.

Data has always been used by businesses to gain insights and strengthen their business. Big Data takes this to next level as it takes more factors into account and does this analysis on a larger scale. If used in the right way, it is a powerful tool for companies to outperform their competitors.