Big Data Analytics Definition and Future

by Jairon Landa

Big data analytics examines bulk data to expose hidden correlation, patterns and other intuitions. It is the process of probing large data sets containing an assortment of data types. Several companies in the world have implemented Big Data analytics to uncover hidden information regarding different variables. These companies and enterprises have reaped many business benefits which include improved customer service delivery, efficiency in the company’s operations, improved marketing strategies and discovering new opportunities to generate more revenue.

The main reason why companies implement Big Data analytics is to enable them to make more informed decisions. It gives analytics professionals the ability to analyze Big data from varied sources. Big data passes new openings to current society and defies to data scientists


Benefits of Big Data analytics

Given how competitive the business world has become, no company should underestimate the advantages of big data analytics. For those companies that know how to leverage the technology substantially, they get a breakthrough for more informed decision making and consequently more revenues. This platform helps the company take and answer more questions and they are allowed the more accurate decision-making process. Big data analytics can also empower workforce and increase productivity.

It helps you and your companies take and answer more questions

Running a successful business is much more about taking and answering questions from customers. You should as well ask yourself several questions concerning the things that customers want, where the customer needs are based, who are your best and the most loyal customers and why some of your customers are taking a different brand. Before the advancement in technology, answering simple questions like where is your 50 best sources of income could take up to 2 months to get an accurate answer. With the introduction of big data analytics, this process could take a fraction of minutes to be complete and accurate.

It makes you Confident in your accurate data

Benefits that Big Data poses to small, medium and big businesses out there cannot be underestimated. Big data analytics has reduced the risks of giving incorrect answers. With the best BI, businesses can gather data from a huge number of sources and reduce the risk of silted and valuable information. If the business leaders are basing their decisions on inaccurate data, then there is a likelihood that the decisions will affect the outcomes directly.

Empower a New Generation of Employees

The difference between profitable businesses and those that are closing up is how they use technology to enhance effectiveness and efficiency. In the past few years, businesses had access to limited data and this means that they could only answer a few questions. Businesses could only make decisions based on the available information. This is the reason why the majority of them experienced implementation issues and if the decisions are implemented, in most cases were unsuccessful. A great Big Data Analytics platform allows businesses to expand the type and the amount of data they are working with.

The above are just a few benefits of Big Data analytics. However, there are thousands of advantages that Big Data will bring to your business. Most of the benefits that will help and leap you to improve efficiency, increase production, enable successful marketing strategies and increase profitability.

Steps and technologies involved in Big Data analytics

Big data tools are especially useful for enterprises and companies because of the absolute volume of big data which is now generated and managed by modern organizations. There are several spits and technologies used in Big data analytics as discussed below.

Data Acquisition

There are two components of data acquisition which includes Big data identification and collection. The easiest step is big data identification which is done by analyzing the two natural formats of data which are born analogue and born digital. Born analogue data is the information which is in the form of videos, pictures and other such formats which relate to physical elements. This form of data identifications needs to be converted into the born-digital format. They can be converted into born-digital data through the use of sensors such as voice recordings, digital assistants and cameras. There are several digital tools which have changed the way analogue data is converted into born-digital data.

Born digital data is the data which has been captured and stored through a digital channel such as a smartphone app and computer tools. Systems keep on collecting a dynamic range of data from users and hence born-digital data has an ever expanding range. This data can provide both personal and demographic business insights. It can also be traceable through the ever-growing technological channels. Born digital data examples include real-time data from GPS tracking systems and web analytics.

The next step in data acquisition is data collection and storage which has been already identified. A new and a safe method should be implemented to keep in charge of the collected data. The process of collecting and storing data is called MAD. MAD stands for Magnetic, Agile and Deep. However, the process is out of range for most of the small enterprises since it includes a significant amount of processing and storage capacity. What this means is that the most common solutions for Big Data Analysis are based on distributed storage and massive parallel Processing which is also known as MPP.

Non-relational Databases

With the dynamics of technological progressions, the massive data sets have also evolved in how and where the Big data is stored. JSON is the most preferred protocol for saving big data in the current technological stage. With this object, the tasks can be written in the application layer to allow better cross-platform functionalities. Majority of the companies are currently using JSON as an alternative to XML as a way of transmitting data between the server and the company’s web application.

In-memory database systems

This database storage system is developed to overcome the time taken by traditional databases to process the information. The system store data in the RAM of big data servers and hence drastically reduces the Storage I/O gap.

Hybrid Data Storage and Processing Systems

This is a hybrid data storage system which provides scalability and speed at an affordable price. It is therefore mid and small-scale businesses. This storage system uses HDFS to store bulk data across multiple systems which are commonly known as Cluster nodes. It has a replication mechanism to make sure that there is an efficient channel of relying on data even during instances of individual node failure. The system uses Google’s MapReduce Parallel Program design as its core. This program design works on the premises of increasing the number of functional nodes over snowballing processing supremacies of specific nodes. HDSPS can also be run unswervingly using existing hardware which has set up its development and fame meaningfully.

The future of big data Analytics 

The market for big data analytics is one of the fastest growing markets in the 21st century. It is not only working as a tool to attract more profits but it is being adopted by even the most unexpected companies. What this means is that the future holds a lot for big data analytics. The growth rate that Big data is expected to reach by 2019 is phenomenal. Big data was worth $122 Billion in 2015 alone. According to IDC, the big data analytics is expected to grow by a staggering $187 billion by 2019. The market is also expected to grow by 50 per cent for the coming 5 years.

India is one of the top 10 countries where the Big Data market is becoming gradually dominance in data analysis. The country alone is expected to watch the market grow from $2 billion to $16 billion by 2025. In addition, the Big Data market in India is expected to be among the top three most protuberant members of the global big data market.

Where will it grow the Most?

Following the above predictions, Big Data is expected to grow in several industries in the economy. One of it is Telecommunication industry which relies on the company’s ability to perfectly identify their audience, connect and interrelate with them. If big data analysis is implemented the right way, it will help the companies pinpoint how their services are being conveyed to their target customers.

Insurance is the other key areas where evolution and the speed of data analysis and presentation are key. With Big data, the insurance industry can expect immediate feedbacks on customer interests and premium management. Big data is expected to grow tremendously in the insurance industry over the coming 5 years.

Healthcare is also expected to implement big data analytics and end up leaping into the benefits associated with their operations. The real estate sector is also highly unpredictable and data-oriented. Big data analytics will bring close efficiency and ease of operations. Real estate has very many variables to deal with in the market, the economy and the ever-changing trends of personal preferences and Bid Rent measures. Big data will not only complement their already existing data analysis tools in the future but also make it easy and convenient to make informed decisions.

About Jairon Landa (@jaironlanda)
Jairon Landa

Backend and Frontend developer, a.k.a full-stack developer.

Kg Bundung, Tuaran

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