Author: Cristiano Cordeiro

From the beginning of the 21st century, with a great demand for technology, the amount of data and information we generate has become huge. Just so you get the picture, studies show that the content generated in the digital world is doubling every two years.

We call this huge volume of data generated on a daily basis Big Data, a term that is increasingly discussed today. From this massive amount of information, comes the opportunity for analysis to generate valuable insights and, through them, help companies and government agencies in decision-making.

In general, Big Data analysis aims to discover hidden patterns, unknown correlations and other useful information that can be used for better decision-making. Therefore, the advantages of data analysis are several, as you can see below.

What are the advantages of Big Data?

The first overall advantage of Big Data is that its technologies give us the ability to interpret large amounts of data at once. With the speed that Big Data can perform analysis, answers are presented to us in a significantly short time.

The second advantage is the ability to analyze unstructured data. Of all the data in the world that has been generated in recent years, it is estimated that 90% is in unstructured formats, such as email, text documents, social media, etc. This capacity to work with unstructured information allows Big Data to analyze different sources, thus increasing its scope.

The third overall advantage is the ability to interpret event trends, helping to visualize future situations. These trends can be economic, product acceptance, or even climatic.

Going a step further, Big Data also has specific perks. To better understand, here goes some examples used by companies from different segments, thus highlighting the advantages of Big Data in different business sectors:

• Financial services: through data analysis, many financial institutions monitor the emotional manifestations of customers on social media, diagnosing dissatisfactions in advance and gaining time to neutralize them before people migrate between institutions, or close accounts, in the case of banks.
• Retail: through data collection and analysis, retail companies often identify customer buying habits and preferences, as well as social and demographic information. With this, they increase sales numbers and develop more attractive loyalty programs. Another example is collecting data from former customers and crossing it with data from products they prefer: discounts on specific products are generated from this, attracting them back.
• Health: the generation of clinical information reinforces precision medicine, allowing for much more accurate diagnoses. In addition, Big Data can help by monitoring the manifestations of a population on social networks and, in this way, predicting possible cases of outbreaks of epidemics and giving health institutions time to adapt.
• Public sector: by crossing people’s data through different sources, public officers can identify scenarios of revenue diversion, money laundering or other financial crimes. Another perk of Big Data is the ability to monitor the population’s level of satisfaction, generating insights for the implementation of new projects or solutions for the detected problems (which would hardly come to the attention of public authorities through traditional communication channels).
• Teaching: Data analytics can help educators identify at-risk students, ensure appropriate student progress, and implement better assessment and support for teachers and principals.
• Manufacturing: through the visibility provided by Big Data, manufacturers can increase the quantity and quality of production, minimizing waste, creating value and contributing to the profitability of their businesses.

In conclusion

Data grows exponentially and, when analyzed and well explored, provides concrete and relevant information to decision makers. The concept of Big Data brings with it all the potential to obtain business insights, which, consequently, will help the company in the task of anticipating the needs of its customers and market.

The concept of Big Data has gained strength, but it is still not as explored as it should be. As shown, there are several advantages obtained when we leave theory because, based on data and concrete information, we can make informed decisions and become able to respond quickly to changes in an extremely competitive environment.

Talking about Big Data is also entering Industry 4.0. If you want to know more about the subject, enjoy being here and read the article Industry 4.0 and how software can help your company. But first, tell us what you think of this post about Big Data and, of course, feel free to share it with your colleagues.

Also, don’t forget: access the Neomind Blog and learn about our other materials!

ReferencesGeoinova, SAS, Unipar, Administrators, Big Data Business and Info Wester

Acronym for Hypertext Transfer Protocol, HTTP is the protocol used to send and receive information on the web, and it’s based on requests and responses between clients and servers. The basic operation of HTTP goes as follows: the client — a browser or device making a request — requests a certain resource by sending an information packet containing some headers to a URL. The server receives this information and returns a response.

How it all began

HTTP has been in use since 1991. The first version of the protocol, called HTTP/0.9, was a simple data transferring protocol in ASCII text format over the Internet. Then, the HTTP/1.0 version was released in 1996 to meet the need to transfer not only text. Richer data, request and response metadata, and content negotiation, for example, were now considered.

The third version, 1.1, was released in 1999. Its release is considered a milestone that set the Internet standard. The HTTP/1.1 protocol, besides solving numerous ambiguities of version 1.0, introduced critical performance improvements.

From the 2000s on, through the boom in Internet usage, the number of devices connected to it grew exponentially. With this exorbitant growth came the need for performance improvements. That’s how SPDY was born in 2009, a protocol created by Google engineers to help overcome HTTP/1.1 performance problems.

These moves caught the attention of the HTTP Working Group (HTTP-WG). In 2015, 16 years after the release of HTTP/1.1, HTTP/2 was born. Without changing the protocol’s semantics, significant improvements were achieved in information transport performance, as well as lower latency and higher throughput.

HTTP/2 Main Features

To better understand HTTP/2, take a look at the following characteristics.

Single connection and multiplexing

HTTP/1.1 is a sequential protocol, where the browser opens only one TCP connection, requests one file, and only after receiving the file it moves to the next one. If a file is too large, or the server processing is too slow, the page can crash. To minimize this issue, browsers usually open multiple connections, between 6 and 8, per server. In HTTP/2, on the other hand, a TCP connection will be persistent and only one per source is needed since parallel requests and responses can request/receive all the necessary files.

This brings a reduction in processing and memory consumption, a reduction in network operating cost, and increased usability. The result is reduced network latency and lower hardware and software costs.

Binary framing layer

This is the core of all HTTP/2 performance improvements, determining how HTTP messages are encapsulated and transferred between client and server. The encoding mechanism has been redesigned without changing the semantics of methods, verbs, and headers. Communication is broken into frames, over a single TCP connection.

Request Prioritization

It enables the browser to request all elements when discovered, communicating to the server its intention to prioritize any of them. This is done through dependencies and stream weights. An example of this is when CSS files and JS files are requested, that with HTTP/2 the browser will prioritize CSS files first, even if its request in DOM order comes after the JS.

Server Push

It allows the server to send multiple responses to the client, from a single request, without the client explicitly asking for it. Imagine the following scenario: a web browser requests a page’s HTML file; the server then responds with the requested file and also sends the CSS file, JavaScript, icons, and other things.

Automatic compression

HTTP requests have headers with important information about the resource and its properties. With HTTP/2 the headers are compressed using the HPACK algorithm, thus reducing the size of each transfer and maintaining and updating an indexed list of the header fields seen earlier. In addition, data compression via GZIP, which needs to be enabled in HTTP/1.1, became standard in version 2.

Data security and encryption

The HTTP/2 protocol has been implemented to work with or without encryption. However, all major browsers declared that they will only support HTTP/2 with encryption, requiring the use of an SSL certificate.

[IMAGEM: Client, SSL Certification, Encrypted Data, Server]

Conclusion

Web applications like Fusion Cloud, through the implementation of HTTP/2, are showing significant performance improvements, with a big difference in page load times, thus enabling a reduction in hardware costs and a better browsing experience for users.

References:
Wikipedia, Google Web Fundamentals, KingHost, HPBN, Apiki.