By analyzing countless interactions, patterns and inconsistencies taking place within an industry, big data drives new innovations, inventive products and enhanced tools to market.
Big data is basically a collection of information collected from the Internet, computers and other devices. This data is stored in systems that are available for analysis. The collection can include emails, videos, web pages, documents, social media posts and sales records. It can be in form of raw textual data or machine-readable formats such as charts.
Here comes the question on when does big data help to push innovation. According to research conducted by Cisco, 87 percent of businesses have already started using the IoT. Nearly 8 out 10 firms (79 percent) use the cloud with almost 10 percent using big data. So basically, there is nothing new about data driven innovation and its various applications in modern times.
Big data will only go past this level if these 3 factors prevail — Artificial intelligence (AI), internet connectivity and open source technologies, which are currently at a rudimentary stage but improving exponentially over the years. Nowadays AI and internet connectivity would help identify whether you are talking to a robot or a human to make decisions and improve your life. And by connecting everything to the internet, you can find new ideas and solutions that you can use in real time.
With so many possibilities regarding application of big data, there has been a lot of interest among enterprises to start using technology for solving problems and finding ways to improve efficiency and performance. There are two types of techniques used, namely
Big Data Analytics
Big data analytics is useful in several areas. First of all, it improves business processes. Every company, organization or firm wants better services and more efficient ways to work. While not everyone wishes to use artificial intelligence or internet-connected gadgets, it is now possible to predict customer behavior by analyzing and predicting their reactions. Thus we need to understand our clients’ preferences and interests so as to provide them with appropriate services. Secondly, business managers can analyze trends in order to stay on the top and stay ahead of each competing player. The third key example is to use predictive models to forecast sales based on future interactions with the customer. They would also come up with suggestions. Finally, predictive modeling can also ensure greater insight into consumer behavior by understanding users and prospects better.
There are two main characteristics of Big Data Analytics:
It integrates different forms of data, like quantitative and qualitative.
The analyst works with unstructured data.
Big Data Insight
To extract value out of big data, organizations require “big data intelligence”, which in simple words refers to the ability of analysts to access the most important insights. Some examples how organizations and individuals can extract value out of big data:
Analytics to deliver targeted ads. Since the huge amount of data involved (a total of 100 billion data points), organizations can understand individual customers and their preferences and use them in relevant ads.
Analytics to track employee attendance. By analyzing how often employees visit their offices, they can identify high-performing companies. A company can thus employ those high performers. Even though collecting data only requires small sums of money, companies can gain benefits by tracking every detail of employee attendance, including location, age, gender, how long one has worked in the company, etc.
Analytics to predict demand. Analysis of historical data can help predict the future. We can take the past data provided by our stores and retailers to predict demand and provide goods and services to match their actual requirements.
Analytics to design the best shopping experience. When looking at hundreds of thousands of images we can identify the best layout, colours and designs of products displayed on the shop floor. It then makes it far easier to pick the right items for our clients.
Analytics to measure risk and profit. Analysts can analyze the cost incurred by running a particular business. Moreover, they can predict how much effort is needed to maintain a certain level of profitability to achieve company objectives.
