What Is Big Data?

Big Data Definition: A big data collection is a collection of data with a huge volume that is growing exponentially over time. Data is so large and complex today that no traditional data management tool can store or process it effectively.

Since companies are spending billions on Big Data technology, hardware, software, and solutions to derive value from their big data, which either lie unutilized or partially utilized due to lack of proper understanding. 

We will discuss what makes Big Data different from conventional storage systems? And how do we access the value out of this humongous amount of information locked within the sphere of “Big Data.”

Big data represents electronic records generated by many types of modern instruments (sensors) like network routers, mobile devices etc.,

As well as from individual persons, who constantly generate big volumes of data about themselves either by publishing it online or just buying products through the internet.

What Is Big Data

Big Data is an umbrella term that includes all very large datasets and need to be processed by a computer system.

It has three big components: Volume, Velocity, and Variety. And big data is not just big; it is big plus more! 

Many of these data sources are highly unstructured, which means that the “meaning” of each datum (such as text) within the dataset may include one or several topics or aspects.  Also Check: What is PLC Programming

For example, sentiment analysis on tweets involves understanding the topic of the tweet and whether it expresses positive or negative opinions about this topic.

Another example is a customer’s purchase history, which includes not only the items that the customer bought and when they were bought.

But also other relevant data like customer profile information (location, age, gender, interests) and information about the seller (location, size of business, type of business).

It is very difficult to process big data technology using traditional data management tools because of all this variety.

Conventional systems rely on well-defined schemas (structured data) and fixed sets of rules for data processing. 

But big data doesn’t fit into these schemas and rules because it is often unstructured and changes over time.

 

3 Components:  Volume, Variety, and Velocity (Big Data Technology)

Volume refers to the large size of big data sets. 

Variety refers to big data’s interactive nature with various formats that can include text, images, numerical values, and video clips. 

Velocity refers to the speed at which big data sets grow, change and multiply

With big data being so big and fast-moving – growing exponentially as time goes on – it becomes impossible for conventional tools such as relational databases (intended for smaller datasets) to manage big data.

With big data, you need an open-source solution or a cloud storage service like Amazon S3 because of exposure to a large number of users & the impossibility of prior planning of resources required.

With big data, you need an open-source solution or a cloud storage service like Amazon S3 because of exposure to a large number of users & the impossibility of prior planning of resources required.

These 3 big characteristics define big data and make it difficult to process using traditional systems. Also Check:  Big Data Companies In India

What is exactly Big Data?

Big Data Definition: Big Data is a term used to describe the large volume of structured and unstructured data that inundates a company every day.

Big data can be anything from Facebook posts to YouTube videos and even Tweets. 

The big difference is that big data comes in such large volumes it becomes difficult to process using traditional tools and systems.

Big Data Characteristics

How Does Big Data Impact Businesses?

Big data has a significant impact on businesses because it represents an unprecedented opportunity to gain insights into customers, products, and operations. 

Big data enables businesses to answer questions that were once impossible to answer. 

For example:

What are the interests of my customers?

What are people saying about my company on social media?

What is the likelihood that a customer will return?

What is the performance of my marketing campaigns?

How do I optimize my supply chain?

The opportunities are endless, and businesses that don’t capitalize on big data will be at a serious disadvantage. 900+ Seminar Topics For CSE

Big Data Solutions

There are two types of big data solutions:

1) Open source: This software is available for free download and use. 

There are various open-source big data solutions available, including Hadoop and Spark.

2) Cloud storage: This type of service allows you to store your big data in the cloud. 

Often, companies use this type of service when they lack the resources and expertise needed to manage their own big data solution.

Both of these solutions have their pros and cons, so it’s important to choose the right one for your business.

Big Data Engineer Salary

To capitalize on big data, businesses need employees with the skills and knowledge to manage and analyze big data sets. 

These employees are in high demand and can command high salaries. For example, a big data engineer can earn up to $180,000 per year.