Big Data life cycle: understand all Big Data phases

Big Data has slowly become part of our daily lives and work without us being fully conscious of it. The huge volumes of data that our online actions generate, our digital footprints, is able to create advantages for those able to analyze and interpret them. Today we’re going to go through the Big Data life cycle, which includes the different Big Data stages.

Besides, you’ll be able to understand first hand the quantity of work and specialization that involves working in a field such as this. A field that presents a constant growth and is constantly on the look for new talents and professionals. Don’t miss a thing! Here we go!

 

Big Data life cycle and stages

The Big Data life cycle can often be described by looking at its different stages. This means everything that is learned, and knowledge extracted from the analysis of data, can generally be used for the next work. As such, the last phase in the Big Data life cycle can feed the first one.

But, what are the Big Data stages? If you want to know, stay with us and find out!

Generation

Obviously, the first thing that needs to happen for the Big Data life cycle to start is the generation of data. 

This happens in an unconscious manner. Both individuals and companies constantly generate data. Every internet interaction, every purchase, every sale, all of them leave data traces.

This is where the magic of Big Data comes in. With due attention and treatment, data is able to generate very useful information for those who can use and interpret it.

Collection

Not all data is useful for a later Big Data analysis process. For this reason, not all data that is generated every day is collected or used.

It’s up to the Big Data specialists to identify which information must be captured and what are the best ways to do so. There are many ways in which it can be done:

• Forms: the forms where relevant data is introduced are a good source of information for Big Data.

• Surveys: surveys can be a very efficient way to collect a big volume of information from a great number of people.

• Interviews: interviews offer opportunities for qualitative and subjective data collection which might otherwise be more difficult to collect.

• Direct observation: observing and monitoring how people behave when they interact with a website or an app is another technique for data collection.

As you can see, this is one of the key stages in the Big Data cycle. This is where the first sifting of the necessary data takes place.

Processing

Once all data has been collected, it must be processed. Big Data processing takes place in the following way:

• Data dispute: in this case, a set of data is cleaned and is transformed into sets that are more accessible and useful.

• Data compression: at this stage in the Big Data cycle, data is transformed into a format that can be stored in a more efficient way.

• Data encryption: at this point, data are translated into a different code in order to be able to protect their privacy.

The simple fact of taking a printed form and digitize it can be considered a method for data processing

Storage

Another crucial step in the Big Data phases is storing the data that have been previously collected and processed.

The most common technique for this is creating databases or data sets. These are later stored at cloud servers or physical storage servers. This depends on each company or organization.

At this stage of the Big Data life cycle it’s important to establish security protocols and make security copies of all data that is going to be stored. It’s a preventative measure in case the original source is corrupted or experiences some sort of compromise.

Management

Once stored, Big Data must be managed. What does it mean? Basically, the management of databases or data sets that have been previously stored.

This means Big Data professionals must organize, store and recover data as needed all across the Big Data life cycle in a given project.

It’s thus a continuous process. A process that takes place from the beginning until the end of the project. It’s, all in all, one of the Big Data phases that gets interspersed with the rest.

Analysis

This is a key Big Data phase. Once processed, stored and managed, it’s time for data analysis.

However, Big Data analysis can be done for data that is not processed. In order to do this, analysts employ different tools and strategies such as:

• Statistical models
• Algorithms
• Artificial Intelligence
• Data mining
• Automatic learning

Each of these strategies is valid for a certain type of specific challenge. Something you’ll learn if you decide to become a Big Data analyst. 

Visualization

Once you’ve analyzed data, another Big Data phase includes the data visualization processes.

This stage refers to the process of creating graphic representations of information, generally through the use of one or more visualization tools.

Thanks to this, later interpretations through Big Data analysis are easier, as visualization facilitates the quick communication of analysis results to wider audiences.

Interpretation

We finally reach the latest stage in the Big Data life cycle. Although, as we stated at the beginning of the article, this is a continuous life cycle that involves different Big Data projects feeding off each other.

The interpretation process can include a description or explanation of what data shows.

Besides, in this part of Big Data analysis the implications of the analyzed data become yet more important.

 

Transform the future, become a Big Data specialist!

Big Data has come to stay. This field is experiencing a continuous growth and constant transformations in order to find new ways to generate opportunities both for companies and governments. Today these are the phases in a Big Data cycle, but tomorrow new strategies and processes may be included in data analysis.

If you want to be part of this future, now is the time to get trained and become a specialist in Big Data. At Tokyo School, we’re specialists in teaching new technologies to professionals. With our course in Big Data you’ll get ready to become one of the most demanded professionals.

Would you like to learn more? Don’t think twice about it! Fill in the form below and get more information about the benefits of getting specialized training at Tokyo School!