Big Data Analytics in Business

Big Data Analytics in Business

The digital space has become an integral part of our everyday lives. Users worldwide have been producing loads of data there. Speaking of numbers, the total amount of data is 2.7 Zettabytes. The data comes from variable sources: transactions, social media, internet applications. The phrase Big Data describes the increasing volumes of digital information.

BigData hadoop

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Big Data Explained

Big data is the enormous amount of data that is hard to analyze and store. It takes the form of structured or unstructured data. Structured data is mostly textual and can be easily searched for (by alphabetical order, numbers, names). Unstructured data is not necessarily a text. Its other forms are video, sound, images.

Big data features include:

  • Volume: the large amount of data.
  • Velocity: an increasing speed of accumulation.
  • Variety: data comes from different sources.
  • Value: it carries useful information for social and economical life.
  • Complexity: it’s difficult to build correlations between data sets.
  • Variability: it lacks in fixed patterns (trigger events cause massive data flow).

Apart from social media and retail, big data gathers in healthcare services, weather forecasting and all-sized enterprises. Many spheres use big data for their benefit, wide analysis or even for the improvement of people’s lives.

This article will cast the light upon big data analytics in business, how companies use it and make data-driven solutions.

BigData collection processing

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How Businesses Can Benefit From Big Data

Big data and business are inseparable. Due to the modern capitalistic system, the competition between companies is huge. With the help of text, video, sound, network and web analytics, it’s easier to achieve valuable insights and to stay afloat. There is a list of ways how data analysis can bring benefits for your business.

Smart Customer Interaction

Companies can guess the future behaviour of customers using the predictive analytics. One of the evident case studies is Netflix user experience. Based on each member’s interests, algorithmic programs recommend shows that are similar to previously watched. The data sources include social features, streaming time, ratings, metadata (the data about data, such as actors’ names and genre). The technology led to less churn rates and more views. Netflix is a good example of a successful contribution in data analytics.

Online Reputation

Social media posts and forums have a huge impact on the business. Customers willingly share their experience and sculpture the reputation of the company. Reading the feedback is important, as well as responding to it and analyzing correctly. Big data and artificial intelligence can track all the comments, sort them by negative and positive. Moreover, such a data-driven solution cuts down the number of employees who would do the job manually.

Effective Expense Reduction

Businesses that collect and analyse data correctly can reduce their costs in different ways. E-commerce companies use big data to upgrade their supply chain and delivery. Amazon has patented the “anticipatory shipping”. Historical data gives the company the necessary information to make a predictive analysis of the future possible orders. Amazon ships products to the clients’ region before they purchase anything! Therefore, time and cost of delivery are reduced.

Easy Hiring Process

How big data analytics in business can help business with recruitment? With data mining and predictive analytics, it’s easier to hire the right candidate. The HR department examines social media activity, resumes, previous work experience and even tastes in reading, using big data. The method removes bias and identifies warning signals. The information about the candidate is collected before they introduce themselves.

Fraud Detection

It’s not only delighted customers and money that matter. Each company needs to secure itself from fraud. Let’s take an insurance company as a case study. Fake reports about accident, arson, injury etc. are made to achieve money illegally. Instant decision making is easier with implemented big data software. Insurance company has the right tools to collect and analyse unstructured or structured data, such as camera recordings, online purchases, medical records.

Although data technologies make business processes easier, there are some hardships to consider.

Big Data Issues

To be honest, sometimes big data analytics in business can cause big problems. The most common are listed below.

  • Incompetent team: the technology constantly changes, and the company needs to hire the best specialists.
  • The volume and nature of data: there is more and more data in the digital universe and your customers’ information always changes. Without proper machine learning the data management is hard.
  • Security: data protection is expensive, yet obligatory. Apart from fraud, a disaster might happen and shut down the servers.

Read more about Pros and Cons of Big Data.

Deep Learning AMIs

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Closing: Is Big Data Worth It?

It definitely is. Benefits outweigh the disadvantages. Today big data technologies and artificial intelligence are team players in all-sized companies. Starting the journey towards something new is always scary. Our website has a useful big data blog, you are welcome to visit it. Besides, we provide big data services that will upgrade your business and help to tackle big data tasks.

Reach out Romexsoft specialists and get a free consultation.

We wish good luck in implementing cutting edge technology in your enterprise. Stay tuned!

Ostap Demkovych
Ostap Demkovych Tech Lead, Senior Application Architect at Romexsoft | AWS Certified Solutions Architect – Associate | Oracle Certified Associate, Java SE 8 Programmer | Responsible for Java development and Big Data solutions.
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