Big Data as the Future of Technology

Big data is the large volumes of data that is used by various companies for their everyday activities and they are predominantly dependent on it for performing their operations smoothly. It would be very difficult for the companies, otherwise impossible, to process any of the functional activities through traditional methods. The term is considered as an art of accessing as well as storing large amount of data that can be helpful in the future for analysis, study, research, decision making and reference as and when required during the course of the business operations. The data is very large, fast, and complex to deal with, in the presence of any age-old or traditional ways. It is a vast field that includes data storage, extraction, and analysis. There are companies across the globe that rely on big data for various business activities.

Expansion

Though big data has been around for a while, it has gained popularity only in the early 2000s when industry analyst Doug Laney brought exposure to the definition of big data as three Vs:

• Volume: data collection and storage would have been such a task in the past. However, currently it is not the same. Collecting data from multiple sources and storing it has become much easier considering the expansion of big data.
• Velocity: with the growth of the IoT, the need for increasing the speed of various processes to meet the tasks within the allotted time is being met by the interference of big data in the activities.
• Variety: data comes in various forms and stored in different forms basis different format. It is again useful to understand the form which will apply to a particular dataset and use the same accordingly.

In addition to this, there are two other dimensions when it comes to big data:

• Variability: in addition to velocity and variety, it is required that the fluctuating as well as the unpredictable data flow is also considered. It is helpful in meeting the ever-challenging needs of the business along with the loads of data.
• Veracity: it is always important to focus on the quality of the data. As the data comes from multiple sources, it is very essential that there is a proper filtering done to the data collected before it is applied to various sources for analysis.

Top Companies That Are Using Big Data

Multi-national companies across the globe rely on big data for their business activities. Big data not only helps in the analysis of a company’s performance but in automation of various processes that lead to building a competitive advantage by all forms in the industry. For any company, the market share and the growth rate matter the most. Introduction of big data has only helped in bringing about tremendous changes in the performance of the companies that it is being used to build a corporate image as well as accelerate their success. Below are some top companies that rely on big data:

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1. Amazon: Amazon has been termed as ‘customer-centric’. While this has more to do with the quality of the services the company provides to its customers in various ways, big data plays a major role in the same process. The company has access to a vast amount of data of its customers, be it their names, addresses, email addresses, banking information, purchase history, searches, and wish-lists, etc. All this information is put in use to provide better customer service and improve its relationship with its customers. A simple example is when an Amazon employee can have access to a particular customer’s information by just entering their mobile number. However, the level of access to sensitive data again depends on the level of the individual looking out for the data.
2. American Express: American Express uses big data to improve customer service standards too. It focuses on analyzing as well as predicting customer behavior by putting big data in practice in multiple processes. Just by focusing on the transaction history, related accounts as well as the policies that the customers have opted for, the company finds sophisticated models for forecasting various levels to customer loyalty. It also uses the similar method to understand the customer behavior. One such example was when it was predicted that about 24% of the customer accounts would be closed in the next four months by adapting the same method of predictive analysis.
3. BDO: BDO is a national accounting and audit firm that uses big data in risk as well as fraud identification during audits. With the introduction of big data, there has been a tremendous change in bringing out an accurate image of the threat involved during audits, which was a tedious process in the past (with the absence of big data) therefore including a rigorous task of continuous interviews, multiple checks involving hours of manpower and reaching out to multiple teams. It has been stated by the consulting director the firm that big data has been very helpful in narrowing down their search while reviewing data for inconsistencies.
4. Capital One: Capital One is using big data for what is most used for and that is, marketing. The company is making the best of its available resource to make sure that anything they offer to their customers is a success. Considering the trends, habits and demographics of its customers, the company determines the most optimal way to provide various offers to their clients, thereby increasing their conversion rates. This not only helps in better conversion or customer relations but also lays a path for an optimized budget allocation and efficient cost cutting.
5. General Electric: GE uses the data from different sensors that are on machines such as jet engines, gas turbines, etc., to find better ways to work towards better reliability and functionality of the related processes. Basis this test, the reports are shared to the company’s analytics team to work on developing tools and techniques that would help building up a mechanism for increased efficiency. As per the estimates of the company, it has been considered that the productivity in the US, by the inclusion of data would boost up to 1.5%, which would help in raising an average national income of up to 30% within a span of 20 years.
6. Miniclip: Miniclip uses big data to improve user experience as they develop, publish as well as distribute digital games across the globe. It is very important for both the company’s growth as well as its reputation to retain customers which would help in making the gaming platform profitable. The exposure of the gaming features to the big data would only help in making good the performance standards of the company in the present as well as the future by considering the reporting, analysis, experimentation and machine learning data methods.
7. Netflix: Netflix in one such online streaming platform that has massive data about its customers. It not only has the name, email addresses and the payment information of its customers but also their preferred searches as well as watch history. This helps in performing an analysis of how the company can understand the habits of its consumers and invest in purchasing copyrights or focus on expanded streaming of certain shows considering that a range of audience would be opting for the same. One such instance is the set of shows that are available as top recommendations basis the country you are viewing from.
8. Next Big Sound: Next Big Sound has made its way through various social media platforms and online music streaming applications to predict the big thing in music in the music industry. The analytical data of the company helps in providing data to the artists for their individual promotion basis the social media popularity and the impact of television appearances. They also work in partnerships with multiple companies that help in spending billions related to marketing as well as sponsorships related to the music industry.
9. Starbucks: Starbucks relies on big data for working on investing in opening multiple branches at selected locations. The business uses various factors such as traffic information, location, customer preferences, area population, corporate or residential, etc. to analyze the estimated success rate as well as the growth depending on the respective factors. It is due to big data that the business can open multiple branches within the same vicinity and still not go into losses.
10. T-Mobile: T-Mobile uses transaction and interaction data to predict future fluctuations of their customers. The company uses both internal data such as billing information as well as external data such as social media information, to work towards reducing the impact of the multiple defects in various patterns and forms, caused to their customers due to reasons whatsoever.

Importance and Benefits

Big data is a revolution in the field of IT. The increase of the big data in multiple companies is leading towards enhancing the growth of the companies and introduction of big data in a variety of forms in companies. Analytical techniques like machine learning, data mining, natural learning processing and statistics are used when working on big data. It helps in having an efficient mechanism that would focus on identifying new methodologies to enable better opportunities that would help in creating an effective as well as a user-friendly environment when it comes to application of big data in both new as well as old means of the respective business. Below are the major reasons why big data is considered as of the efficient ways for an organization:

• Reduction in costs: when it comes to storing large amount of data, big data technologies such as Hadoop help in bringing in a significant cost advantage to the user.
• Quick and better decision making: with the memory storage and speed, it is easy for the users to make decisions quickly.
• Better products and services: with the ability to provide the best customer satisfaction by easily understanding the needs through data analytics.

Big data is beneficial in various fields and is going to clarify the various keys to work around with the same. There are some industries that have seen an enormous growth with the introduction of big data, such as banking, technology, consumer, and manufacturing. Big data has brought some major changes in the education and research sectors too. In addition to this, there have been some tremendous changes in the fields of investment, engineering, analytics, and software development too. As a result, there is an increase in both competition and demand for the big data professionals as there is a lot of scope and one would see huge potential in it. Also, at the same time one has to understand the best way of using the analytical tools in order to get the best out of the available technologies as well as the resources.

Methods of Analysis

As per a study, the big data market is all set to increase from $42 billion to $103 billion by year 2027 globally. It is clear enough that the entire world is driven by data. One can simply not understand how the data is overtaking the lives of everyone in unexpected ways. Be it using google maps to track something down, online shopping applications, looking out for restaurants open near you, getting all the details by just scanning a QR code, etc., big data plays a major role in various activities that are a part of one’s day-to-day life. A survey by McKinsey stated that when an organization uses the data, it is going to be beneficial to both businesses as well as its customers with the various data-driven strategies and the business models that it practices. It is a matter of fact that every year, up to 2.5 quintillion bytes of data are created and it has been observed in the last two years that 90% of the data has been generated, at a global level.

Data analysis is the method of examining the existing data sets and drawing conclusions about the information they contain. The report by McKinsey states that the techniques and technologies used are very wide in number considered for the fields such as computer science, statistics, mathematics, and economics. The analytical tools can be applied to both big data as well as smaller datasets. Below are some of the techniques that are used for the analysis of the big data:

1. A/B Testing. This technique involves comparing one control group with various test groups to understand what changes could be made to improvise the given objective. Big data is a perfect fit as it can test huge numbers, yet the catch is that it can happen only of the groups are big enough to provide greater differences. Example: Humana, an insurance company that focused on bringing in some major changes and huge results by conducting the test twice. It is just a proof that one test is not enough at times.
2. Data Fusion and Data Integration. By working towards achieving efficiency regarding the combination of the techniques to analyze as well as integrate the data from multiple sources, potentially accurate if achieved from a single source. It is a combination of both ETL process and the execution of the same. Example: Database management process.
3. Data Mining. It is a commonly used tool that works by extracting data from large data sets by working on a combination of multiple methods of database management. Example: Mining customer data learn the amount of people that would react to a particular offer it put on the website.
4. Machine Learning. Though popular with the artificial intelligence, machine learning is used for data analysis too. It works with the computer algorithms to provide any assumptions basis the data. The predictions by machine learning are something that are impossible to be carried manually. Example: Finding credit worthiness of the business.
5. Natural Language Processing (NLP). This tool uses algorithms to analyze human language is considered the subset of artificial intelligence. It studies the patterns through various ways and extracts significant relationships context of response. Example: Finding out what customers are trying to say with the data from their posts.
6. Statistics. Statistics is all about collection, organizing and interpreting data for the application to various techniques. Example: Collecting data every year to understand the changes in the population and the rate of increase on a yearly basis.

Conclusion

Big data is the future of technology and any organization that relies on big data for the same is going to make big money considering the amount of impact it has on the activities related to the organization and its value. Innovations is about finding some major impacts onto the growth of the changing needs of the business. Big data not only helps an individual in having a better profile such as greater job opportunities and increase in the growth but also on an overall basis. With the use of all such techniques, it is helpful for all the companies to in expanding their scope and working on achieving better results.

References

1. Big Data Insights. (2020). SAS Insights. Retrieved from https://www.sas.com/en_us/insights/big-data/what-is-big-data.html
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3. Syed Junaid Hussain. (October, 2019). Medium.com. What is Big Data & Why is Big Data important in today’s era. Retrieved from https://medium.com/@syedjunaid.h47/what-is-big-data-why-is-big-data-important-in-todays-era-8dbc9314fb0a
4. Getsmarter. (February 2019). GetSmarter.com. Big Data Analysis Techniques. Retrieved from https://www.getsmarter.com/blog/career-advice/big-data-analysis-techniques/
5. The Daily Egg. (March, 2019). Crazyegg.com. 3 A/B Testing Examples That You Should Steal. Retrieved from https://www.crazyegg.com/blog/ab-testing-examples/