21 NOV 2017

Analyzing Big Data: advantages, opportunities and management

The theme of Big Data is very current today, we talk about it both at the company level and at the Public Administration one, but it is not always clear what Big Data is used for, how to store it and how to manage it.

We have done a bit to define and clarify Big Data, its use, the potential of a structured analysis and the evolution of market scenarios with the increase of Big Data volumes.


What is Big Data and what is it for?

Big Data has 3 main characteristics, called the “3 V”:

  • Volume:  refers to the large amount of data available;
  • Velocity: refers to the time necessary to collect, process, archive and analyze data;
  • Variety:  refers to the types of data which can be structured, unstructured or semi-structured.

When you are working with Big Data, it is important to know the essential aspects of the process to gain a competitive advantage. Time is crucial because it is necessary to carry out the analysis in a short time: in order to do so, database design is important, because experts know that one of the biggest problems is the amount of time to access data.

In terms of variety it is necessary to identify the type of data to work on and we can have:

  • structured data: data that must be written respecting a precise framework;
  • semi-structured data: it doesn’t have a precise framework, but there are certain rules to be respected in its construction;
  • unstructured data: there are no rules for writing this data.

Generally, the data of a database which comes from a single source is mostly homogeneous in its form, this is almost never true if data comes from different sources: videos, images, sounds, and texts, are all examples of data, but each one it is written differently and analyzing unstructured data is more expensive than structured data.

Over time, however, two other characteristics of Big Data have been identified, another “2 v”, added to the previous ones. They are the Vs of:

Veracity: refers to the quality of data, it is important that the data is of good quality, that is it is not damaged, incorrect or compromised. Low quality data leads to financial losses.

Value: refers to the ability to transform data into valuable information that can be used for specific purposes.


Big Data analysis, an example

Let’s consider an example to better understand the types of analysis that can be done on Big Data. Previously, in the case of traditional advertising through a television commercial broadcast on a given transmission, the only data that we could obtain about the diffusion of the spot was relative to the number of spectators, but it was not clear how many of these belonged to the target of the product. Today, with internet advertising, it is possible to obtain detailed information not only about the number of users, but also it is possible to obtain their detailed profiling.


Big Data, who uses it and why

Big companies like Google, Amazon, Facebook and Netflix are building their fortune on the analysis of available data. For example, Netflix decided to produce the TV series “House of Cards” based on the information in its database, which collected the preferences of its customers in relation to the rental of films.


How Big Data volumes can grow?

The volumes of data held by companies is destined to grow more and more, thanks to the arrival of the Internet of Things: a lot of devices, such televisions, refrigerators, heating and cooling systems, are connected and controlled via Internet and they produce more and more data, each time in greater detail. By 2020, according to Gartner, it is expected that over 25 billion objects will be connected to the Internet.

It is estimated that in 2020 there will be 35 zettabytes of data (that is 35 thousand billion gigabytes).


How can Big Data analysis help a company?

The analysis of Big Data for business purposes falls within the Business Intelligence process and is fundamental for a company if it has a large amount of data. In this case, the company could have great benefits from its analysis. Analyzing available data, the company can become more competitive: the analysis of Big Data allows evaluating the risks and potential of a market, understanding customers’ needs, and optimizing its activities in order to reduce costs. The public sector, as well as the private sector can benefit from the analysis of Big Data, especially Public Administration. In Public Administration, an immediately clear example of the benefits of analyzing Big Data relates to the Healthcare sector. The analysis of Big Data would be beneficial from the perspective of analyzing costs, prevention and much more.


How many times can the same data be analyzed?

Data analysis leads to the discovery of relationships and hypotheses that must be verified by further analysis. This process can be repeated many times, depending on the size of data.

Big Data analysis includes 2 main phases:

  • Big Data Management: the set of processes and technologies for acquiring and storing data;
  • Big Data Analytics: the set of processes used to analyze and transform data into information quickly.


How to make data understandable to laypersons?

In order to accomplish this, the Data Scientist is important. Using visualization tools and machine learning algorithms, the Data Scientist is able to interpret data and to acquire useful information which can be transformed into visuals or infographics. The old proverb “A picture is worth a thousand words” is particularly true in the analysis of data, big and small!

How do you imagine the future evolution of Big Data analysis for companies?

Right now, many companies are interested in the topic of Big Data: these companies have a large amount of constantly growing data which must be analyzed quickly to obtain a competitive or economic advantage, in order to provide new services, as in the case of the Public Administration, to improve the national system. We are at the beginning of a new era in which new technological trends, including Big Data, but also Cloud, IoT and the availability of open or low-cost platforms, allow us to accelerate projects and change our daily lives. In this context, as a company, we expect that Big Data, and the heterogeneous sources responsible for its production, grow exponentially and for this reason it will always be more difficult to determine the levels of data confidentiality, establish how to access to data safely and decide where to place critical information. The world of Big Data is opening new technological scenarios in which cybersecurity, which has always been part of Consulthink’s DNA, is going to play an increasingly important role.

Elaborated by Lucia D’Adamo, in collaboration with Luigi Laura, supervised by Marco Pirrone

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