In today’s era, numerous social apps are being developed which result in increasing data massively every day and when we talk about social media platforms , millions of users connect on daily basis , information is shared whenever users use a social media platform or any other website, so the question arises that how this huge amount of data is handled and through what medium or tools the data is processed and stored. This is where Big Data comes into light.
In this blog I will demonstrate the importance of Big data and what big data tools and techniques are used today.
Big Data :
So the first question is what is Big data?
Big data is a term that describes the large volume of data — both structured and unstructured — that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters. Big data can be analyzed for insights that lead to better decisions and strategic business moves.
Still not sure what Big Data is? The IT industry, in an attempt to quantify what is and isn’t Big Data, has come up with what are known as the “V’s” of Big Data. The foundational three are:
- Volume: The amount of data is immense. According to sources each day 2.3 trillion gigabytes of new data is being created.
- Velocity: The speed of data and processing (analysis of streaming data to produce near or real time results)
- Variety: The different types of data, structured, as well as, unstructured.
The concept of big data has been around for years, most organizations now understand that if they capture all the data that streams into their businesses, they can apply analytics and get significant value from it.
When a company has TBs data of every month so its necessary for them to analyze that data and get desired results from it, but working on such a huge amount of data is not possible with ordinary tools however if some how you get to work on those simple tools it would take days to get accurate results. Thats why Big data tools are used to handle that data and get accurate results in a short period of time.
Definition of Big Data according to different Sources :
According to Gartner:
Big data is high-volume, high-velocity and high-variety information assets that demand cost-effective, innovative forms of information processing for enhanced insight and decision making.
Big Data is a broad term for data sets so large or complex that they are difficult to process using traditional data processing applications. Challenges include analysis, capture, curation, search, sharing, storage, transfer, visualization, and information privacy.
In Big Data, a Revolution, authors Viktor Mayer-Schönberger and Kenneth Cukier, offer no rigorous definition of Big Data, but offer insight as to why the size does matter, and what it can be used for:
“The ability of society to harness information in novel ways to produce useful insights or goods and services of significant value” and “…things one can do at a large scale that cannot be done at a smaller one, to extract new insights or create new forms of value.”
Importance of Big Data :
The Big Data analytics is indeed a revolution in the field of Information Technology. The use of Data analytics by the companies is enhancing every year.Big data has the properties of high variety, volume, and velocity.Big Data involves the use of analytics techniques like machine learning, data mining, natural language processing, and statistics. With the help of big data multiple operations can be performed at a single platform. You can store Tbs of data, pre process it , analyze the data and visualize the data with the help of couple of big data tools.
Data is extracted, prepared and blended to provide analysis for the businesses. Large enterprises and multinational organizations use these techniques widely these days in different ways.
Big data analytics helps organizations to work with their data efficiently and use that data identify new oportunities. Different technqiues and algorithms can be applied to predict from data. Mutliple business strategies can be applied for future success of the company and that leads to smarter business moves, more efficient operations and higher profits.
Following are the three main reasons that why Big data is so important and efficient.
Cost reduction. Big data technologies such as Hadoop and cloud-based analytics bring significant cost advantages when it comes to storing large amounts of data
Faster, better decision making. With the speed of Hadoop and in-memory analytics, combined with the ability to analyze new sources of data, businesses are able to analyze information immediately and make decisions based on what they’ve learned.
New products and services. With the ability to gauge customer needs and satisfaction through analytics comes the power to give customers what they want.
Real-time Benefits of Big Data Analytics:
The use of Big Data analytics is very flexible to another fields as well. With the use of big data alot there has been an enormous growth in multiple industries. Some of them are
Specially in Banking sector, big data tools have been associated with their system. Multiple operations can be performed on transactional data moreover tools like Apache Hive facilitate users to query on their data to get results in a very short period of time. A user can optimize the query engine to get better query performance.
The usability of big data is also increased in educational sector. There are new options for research and analysis using data analytics.The insights provided by the big data analytics tools help in knowing the needs of customers better.
Job Opportunities and Big Data Analytics:
With huge interest and investment in the Big Data technologies, the professionals carrying the skills of big data analytics are in huge demand. Fields like Data Analytics and Data Engineering have the most worth now a days. IT Executives , Business Analysts and Software developers are learning big data tools & techniques to grow with the market of jobs & opportunities since some of the big data tools are based on Python and Java so it is easier for the programmers who already working on these languages moreover users who know how to pre-process and has skills like data cleaning, can easily learn about Big Data analyzation tools and analytics. With the help of visualization tools like Power Bi, Qlikview, Tableau etc , a user can easily analyze the data and present a new marketing strategy.
In different domains of industry, the nature of the job differs and so does the requirement of the industry. Since analytics is the emerging in every field, the workforce needs are equally enormous. The job titles may include Big Data Analyst, Big Data Engineer, Business Intelligence Consultants, Solution Architect, etc.
The importance of big data analytics leads to intense competition and increased demand for big data professionals. Data Science and Analytics is an evolving field with huge potential.There are huge requirements and significance of big data analytics in different fields and industries. Hence, it becomes essential for a professional to keep oneself aware of these techniques. At the same time, the companies can gain a lot by using these analytics tools correctly.