Extensive Guide for Big Data | Big Data Analytics

In simple terms, Big data is a term that describes a relatively large amount of data gathered, which is hard to assemble and manage without necessary operational tools. Just by the name, it is big and complex, but in actuality, its definition of Big data is more diverse than its names, so let's answer the 3Ws (Why, What, and How) of Big Data. Finally, you will get a bird’s eye view of Big Data and its application in different industries.

What is Big Data?

According to big data definition, big data combines different types of structured, unstructured and semistructured data. Organizations collect them in huge amounts to perform better business decisions, strategies, and actions.

The big data is mainly mined through a large audience, annual performance reports and competitors reverse engineering for the targeted market analysis, machine learning projects, and predictive modelling to achieve a competitive advantage.

How and Why Do Organizations Collect Big Data?

When speaking of how Big Data is collected, multiple systematic tools and strategies are followed to get the desired results. Email marketing, asking for data and cookies/web beacons are few main elements to gather data. But every organization could demand different types of data, like traders may need data of open trades from all over the world. They will figure it through multiple functionality and tools based systems. At the same time, an eCommerce owner can do an online survey to know the need and demands of his product.
Why companies gather big data could be answered as every field has different aspects to follow. However, the main concern for every organization is to mine data that can generate valuable information to help them create winning strategies for their companies.

Technologies Used in Big Data

Big data is enormous, and the amount increases exponentially, maybe every hour, day, week and year. So getting that much versatile data fitting into one canvas is not a piece of cake: an organization needs to use technology. It would be crazy to say that we can have complex data organized in MS word or excel. These are essential tools that can be used for fundamental data analysis and entries. When it comes to dangerous big data, the collector needs special analyzers tools, data extracting and data protection. Big data technologies use all this software and tools to help an organization analyze, obtain, organize, maintain, and retain data.

Big Data Analytics and its Features

What is big data analytics? The word sounds easy, but only the dish is easy, not the task we need to bear along with big data analytics. Big data technologies make it possible to have its analytics reports as it is made accessible due to optional extensive data tools availability. These tools help an organization, individual and startup to have data that can bring success. In simple words, they analyze huge data and not possible for a simple data entry tool to diagnose or perform the action on it.

Big data analytics takes out everything from data that can help gain exposure to clients, customers, or services. And big data tools allow us to perform corresponding extensive data analysis to gather the best out of big data.

Few Features of Big Data Analytical Tools

Humans have traits that differentiate them from others; like humans, tools and software have features/functionality that provide them with an edge over one another.

Data Processing

I assume that you read the above information and know what big data is. So now we know that big data could be in several forms like structured, unstructured and semistructured. We can call all this together that it is in rough condition when an organization gathers big data. The first step they need to take is data processing, which means making something out of raw material. Differentiating all the data according to its value and composition is called data processing. Many big data tools are available to help you process your raw data into valuable content.

Reporting Big Data

This is a live data gathering system. The organization can analyze its user's activity according to time, country and language etc. Live reporting can create big data of behaviour that could be used for targeted marketing. It could use it for country-wise market analysis to know how their products or services are demanded in different regions.

Google Analytics is the best example for website owners. This tool provides in-depth behaviours of web visitors, their time spending, and session.

Security Features

Big data acts as a backbone when it comes to developing strategies for a firm. Extensive data mining is a super-secret for competitors, so it needs to be secured so no one can have the same data.
Big data could be the same, but after data processing, the data is converted into rare points to make a solid marketing plan or strategy for product launch. Big data tools are entirely safe to use. They have built-in security features to keep your data safe and secure from attackers. Some people may question “big data dangerous issue”. As long as organizations utilize the right big data tools to deal with the data collected from users, you can overlook such a problem.

And the list goes on few mentions as they are primary point:

• Data mining and file exports
• Source file hunt and modelling application
• Fraud analytics check and identity verification
• Risk and decision management
• Stats, content and predictive analytics
• Dashboard compliance for direct reporting
• Location and language-based insights/reports
• Secure data encryption
• Technological support

Big Data Applications in Different Companies

Big data uses are way more than we think; firms with product selling gather big data of their potential customers to run ads campaigns and boost conversion.

• Doctors and researchers use big data to comply with any disease report or make new medicines based on disease symptoms and effects on attacked patients.
• Oil and refinery companies use location-based data to discover more resources and places to find resources with the help of previous reports.
• Website owners can analyze the behaviour of their visitors and add value by adding user-friendly content.
• Service offering firms use big data for providing better customer support to make them permanent clients.
• Financial companies have vast big data applications to help render investment chances.
• Transportation and manufacturers use data to improve their supply chain and enhance their delivery routes for fast actions.
• And the government also uses big data in the application for emergency response and crime prevention etc.

Leading Companies Adopting Big Data Intelligently

There are thousands of companies that are providing big data to firms for their usage. A few are.

• Google
• DISCO
• FOURKITES
• Starburst Data
• IBM
• Salesforce
• Cloudera
• Segment
• Crunch base

Big Data Pros

• Help to target potential customers
• Maintain a good position in the competitive market
• Choose versatile data to reach your success
• Create strategies that can perform better
• Big data helps in enhancing your firm value
• Vast applications in every field

Big Data Cons

• Time-consuming process
• Need to buy extra tools
• No privacy of customers' data

Conclusion

Big data has vast application for every firm and in nearly every aspect of life from food to med. Every person needs data to console their potential customer's requirements. However, they do have few outcomes mentioned in the cons.

So write your benefits in the comment section to let us know whether we could satisfy the need or not?

FAQs

To finalize this guide, we’ve collected some Frequently Asked Questions that revolve around Big Data.

What is big data used for?

Big data is the set of technologies used to store, analyze and manage this bulk data, a macro-tool applied to identify patterns in the chaos of this explosion in information so as to design smart solutions and provide better services. As Big Data continues to permeate our daily lives, there has been a significant shit of foucs from the hype surrounding it to finding real value in its use.

Most organizations have several goals for adopting Big Data projects, among which the primary goal for them is to enhance customer experience, other goals involve cost reduction, better-targeted marketing, and bringing more efficient processes. In recent times, data breaches have also made enhanced security an important goal that Big Data projects seek to incorporate.

Here is a list of the top 10 industries that use big data applictions:

• Banking & Securities
• Communications, Media and Entertainment
• Healthcare Providers
• Education
• Manufacturing and Natural Resources
• Government
• Insurance
• Retail and Wholesale Trade
• Transportation
• Engergy & Utilities

How is big data collected?

In general, there are three common ways that companies collect data about their users. By asking them directly for it, indirectly tracking them, and by acquiring it from other companies. But most companies will be asking users directly for data at some point.

What are the types of big data?

• Structured Data
• Unstructured Data
• Semi-Structured Data
• Subtypes of Data
• Interacting with Data Through Programming

Is big data dangerous?

Big data comes with security issues. In specific, security and privacy issues are the key concerns when it comes to big data. If data falls into the wrong hands, users’ personal information will face risks. Otherwise, there is no need to worry about data security. In a nutshell, users shall distinguish between truth and falsehood.