Roaming around to promote themselves and delivering a boring speech in front of an uninformed audience is quite a passé way of campaigning now as per political giants. Today, as the public have changed and are taking ample interest in knowing their preferred political leader, major political parties are also playing smartly in terms of communicating with the public in a better way and understanding their views, by utilizing Big Data.
Statista claimed that the global Big Data market is estimated to grow to 103 billion U.S. dollars by 2027, which is more than double the expected market size in 2018. Emphasizing the growing importance of big data, Geoffrey Moore, an American consultant opined that – “Without Big Data, you are blind and deaf in the middle of the freeway.” The impact of big data applications is loud and clear – from comprehending the thinking of the general public to enabling businesses to flourish. Big data for Businesses (whether it is a large company or start-up) acts like wonder!
How businesses are using big data?
- Walmart – With big data, businesses can understand the requirements and preferences of their customers more precisely, the biggest example of which is the world’s largest retailer – Walmart using big data analytics since the world barely knew about big data. Maximizing the shopping experience of the customers followed by achieving increased customer conversion rate is what primarily Walmart attains by applying big data.
- Uber – Have you ever noticed the surge in cab fare in the peak hours or rainy days when the demand for the cab is higher? This is all because of the vast data collected by the cab service which helps them to know the appropriate time when the fare should be on the higher side. On that account, Uber is one of the biggest cab services which utilize big data.
How does Uber use big data?
It keeps a track on the drivers’ database, demand in different areas and varied information with the help of big data.
- Netflix – Ask any millennial (or even aged people) the importance of Netflix in their life and they will tell you how Netflix helps them to deal with the mundane life. But here the question is how does Netflix always come up with content which can match up to the expectation of the audience? Here’s where big data comes into the picture.
How Netflix uses big data to drive success?
Netflix decides its content be offered based on its ‘recommendation engine’ which is driven by data analyzing its customers’ choice and inclination.
- Amazon – Does your favorite e-commerce app have ever sent you a pop-up text of the product you view sometime or a few days ago? If yes, then this is because of the implication of the big data by e-commerce companies which continuously tracks your searches and wish list followed by frequently reminding you to go back to the app and purchase the product. Amazon is a prominent player in the e-commerce space and it admitted that using big data in providing shopping recommendations to its customers has increased its revenue manifold.
- Facebook – This write-up would be incomplete if we don’t mention Facebook using big data. From letting the users view advertisements based on their preferences to reminding every user’s birthdays, special memories and similar events, big data plays an essential role in the operation of Facebook. Likewise, other social media platforms such as LinkedIn and Instagram as well apply big data for catering to its users’ needs.
While it’s true that the benefits of big data in business are huge, this also can’t be denied that it has remarkably increased the demand for skilled big data professionals. If you’re interested in learning big data, which is counted as one of the most demandable IT courses, get yourself enrolled today, because its worth your time and investment!
As the years pass on the volume of data which needs to explode had been increased to unimagined levels.
This process of collecting raw data from different sources and making them useful for the benefit of an organisation can be termed as big data analytics.A traditional big data life cycle:In order to organize the data from an organization, you need to create a framework with different stages of life cycle for big data analytics.
All the stages in the data life cycle are connected to one another and can be distinguished into traditional and statistical methods.CRISP-DM Methodology:CRISP-DM stands for Cross Industry Standard Process for Data Mining Methodology.
You need to perform the tasks simultaneously.Modelling: In this phase, various modelling techniques are used and applied to the parameters to attain optimal values.Evaluation: In this phase, you need to build a high-quality data analysis before deployment.
SEMMA focus on the modelling part whereas CRISP-DM focus on all the stages of the big data life cycle.
In some of the approaches, you can find some incomplete data.
Increased number of Internet users, popularity of social media, and ability to easily share unlimited information over these platforms has resulted in generation of large amounts of data on a daily basis, which is projected to augment demand for big data solutions over the coming years.
Extensive usage of cloud technology has also generated significant volume of information due to enhanced connectivity and technological developments, thereby providing the market a major boost.On the other hand, lack of skilled manpower, which is needed to leverage big data capabilities, may have a negative impact on market growth.
Nevertheless, the industry is emerging as a highly lucrative option for many end-use sectors as this technology allows companies to manage large data volumes in an effective manner, resulting in overall cost reduction.
The emergence of this technology has given opportunities to a number of businesses to monitor valuable information and convert it into a significant usable insights.
The storage segment is expected to witness significant growth as a result of rising demand for public and hybrid cloud solutions.
It is also used in brand reputation, predictive analysis, and relationship management.On the basis of region, developed regions such as North America and Europe have been major markets due to government focus on improving operational efficacy.
