90% of the existing data have been generated in the last two years. Around the world, almost 4 billion people are active on the web and around 3 billion are using social media. Every day a single user generates on average 12 gigabytes of monitored data in real time.
These are some of the significant numbers that emerged from the surveys and reports developed by Global Overview, more simply summarized by the term “Big Data”. Interactions on Social Networks, clicks on web pages and searches with smartphones are not, in fact, only actions carried out daily by a very large number of people, but constitute the origin of innumerable heterogeneous data conceived and simultaneously evaluated: all this is the Big Data.
In order to have a true idea of the immense quantity of data considered, it is sufficient to think that Big data are calculated in Zettabytes, units of measurement corresponding to billions of Terabytes, and that they are data coming from heterogeneous sources: they can be structured relationships derived from a database, but also information obtained from the web or from social networks.
The Big Data, being a phenomenon strictly dependent on the uses and habits of consumers, constitute a fundamental tool for companies in order to develop innovative and competitive business models: by analyzing the online behavior of the consumer, the company can obtain information additional, more precise and detailed to be able to design more effective and personalized marketing and communication campaigns.
Big Data: The 5 main features
What are the characteristics of Big Data? Is the size enough to define them?
The only criterion of the volumes is not clearly exhaustive to characterize the Big Data, it is, in fact, important to consider other types of characteristics such as the variety of formats or the average speed of analysis, but even more so five peculiarities that usually characterize Big Data …
Volume is the first distinctive feature of Big Data: as already stated, companies collect a huge amount of data from every type of online source. Storing such a large number of data in the past would have been impossible, but today, thanks to new technologies such as Cloud and virtualization, it is possible to store data and access it for every kind of need. According to market analyzes, by 2020, 35 Zettabytes of data will be created, or 35 trillion gigabytes;
Big Data is generated, transmitted and analyzed in a timely manner and at an unprecedented speed since, in order to be useful for optimizing a business strategy, the data must be current and truthful;
The types of formats that Big Data present are heterogeneous: they can be numerical and structured coming from classic databases, unstructured text documents, emails, images, videos, web searches or financial transactions. The diversity of these data and the origin from different sources allow companies to structure communication and marketing strategies based on the habitual actions of consumers and therefore largely customized;
Similar information and data take on diametrically different meanings depending on the virtual context in which they are found. It is necessary to contextualize each data to understand its importance and function;
Big Data is in continuous and immense growth and for this reason it is essential to distinguish truthful data from data collected from unreliable online sections. True and reliable data can be a fundamental tool to increase the profit of your business.
Big Data: Why are they important?
Big data collection and analysis allows companies to develop competitive and innovative business strategies and models that can constantly improve. In fact, studying this data allows you to make targeted business decisions in order to increase the number of potential customers and therefore sales, to make customer loyalty strategies more efficient and to devise cross-selling and up-selling strategies studied in based on user needs.
It is the technological skills of Analytics that transform the raw data received from the system into valid and interesting information for corporate decision makers: in a market in continuous development and change such as online, it is fundamental for companies of any type and size to take timely decisions.
Big Data: How can they help your company?
All over the world the Big Data market is now a consolidated business, in fact, even data is constantly growing: the Big Data Analytics & Business Intelligence Observatory highlights the positive trend of the last three years also in 2018, reaching a total investment of 1.393 billion dollars, up 26% compared to the previous year. The Big Data business exists and is evident.
Why do companies invest in big data?
- The data collected helps the company to understand how users perceive a brand and how they react to markets: by analyzing the data, the company can gather a large amount of information regarding the effectiveness of the communication strategies adopted and therefore inherent to the trend company itself;
- Big Data make a company able to segment its user base in order to significantly customize the marketing and sales strategies implemented. Knowing and differentiating the purchasing behavior of users are essential actions for a company with a good online market;
- The data collected identify the key factors that move people to buy a specific product, allowing companies to leverage on the most profitable market choices;
- The study of Big Data allows the effectiveness of individual media to be examined in order to identify which platforms are the most appropriate for communicating a given content;
- The information collected enables the design of predictive simulations to understand how the market in which the reference company operates will evolve;
- Data analysis can enable new business models based on innovative purchasing trends recorded in real time.
Big Data Analytics: Business methodologies for analyzing data
The use of technological tools and innovative methodologies of data analysis is fundamental to make the profits of your business grow and make it more competitive online. There are four types of analysis to study Big Data …
- Descriptive Analysis: Methodology that, through the use of graphs and performance indicators, allows to describe current and past situations concerning business and business processes;
- Predictive Analysis: Technique that focuses on in-depth analysis of the possible eventualities in the future within the reference market thanks to the use of mathematical formulas and algorithms;
- Prescriptive Analysis: Study used to identify effective strategic and operational solutions;
- Automated Analysis: A tool capable of implementing any desired action autonomously and in a totally automated manner based on the strategic choices identified by the company.
Big Data Analytics: The goals achieved
There are significant data examined by the Big Data Analytics & Business Intelligence Observatory regarding the actual objectives pursued by companies that already invest in Big Data Analytics strategies …
- Improvement of customer engagement;
- Improvement of the company web reputation;
- Sales increase;
- Reduced purchase time;
- Optimization of existing offers and creation of offers regarding new products;
- Cost reduction;
- Insertion in new markets.
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