Discover how to face the new Big Data generation with Cloudera

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New frameworks, new utilities, new use cases. Big Data technology advances and evolves as much as the technology sector as a whole. In this post we are going to talk about the new trends in the Big Data market and how Cloudera’s solution in this technology has been transforming itself to provide the best response. And, fundamentally, to make this technology as accessible as possible to all those companies that want to get on the train of business modernization and transformation.

If you want to know Cloudera’s technological proposals in Big Data and how they facilitate the use cases that organizations are encountering today, don’t miss the “Big Data Next Gen” talk by Sergio Rodríguez de Guzmán, CTO of PUE. In his exposition, he leads us to understand, in a key perspective, not only how Big Data has been understood and conceived until now, but also what the current challenges are and the new bases of that generation that comes in this technology and that has been changing with the passing of time. pass of the time. You will find it in the following video:

What are the pillars of the Next-Generation Big Data?

Many of the fundamentals that Sergio defines in his video are based on the premise of Open Source Software development as a pillar for building architectures. This implementation helps modernize processing times and the variety of use cases regarding Data Warehouse and DBI environments without replacing the latter.

Let’s get to know the pillars and most outstanding aspects of the new Big Data generation, as information to be taken into account by any company that is considering an implementation of this technology:

  • The flexibility based on Open Source, which promotes technological evolution that does not exist in other more hermetic ecosystems.
  • The democratization of the source of the data, that is, the new generation of Big Data must take into account that any smart device, loudspeakers, lighting, are possible transmitters of data that will have to be analyzed. This implies the need to extract and expose information securely through APIs for internal consumption or for third parties.
  • The location of the data based on the processing core loses importance.
  • The volume of data flow is greater, making it essential to use correct data treatment and an adequate infrastructure for extracting information according to who needs it.
  • The extraction of information from files or relational gives way, with Big Data, to all kinds of information sources, such as video processing, images and binary formats with any origin.
  • In the new generation Big Data, the data can reside in public Clouds or in hybrid Clouds.
  • It guarantees the security and reliability of the data, since it is distributed in object storage, which simplifies backup and recovery tasks.
  • Physical environments and nodes are replaced by practically all the nodes that are part of the Big Data ecosystem, for the part of infrastructure, data intake or information production that become virtual. This fact ends up transforming all the bases of Big Data technology as they had been proposed until now.

What challenges does the new Big Data generation pose?

There is something inevitable, and it is the arrival of immediacy as a must in Big Data. The information is generated, consumed and analyzed in real time, which requires fluidity through the different producers, sources and data origins. Given this need, all methodologies are oriented to this functionality in real time. For this reason, the platforms have to be prepared to deal with the ingestion of this data and to encourage decision-making in real time as well.

When choosing a Big Data provider, there are some vital parameters to consider:

  • Select a good service provider. With proven expertise.
  • Identify who offers a better proposal at the architecture level.
  • Bet on a flexible solution so that the service is scalable.
  • To be able to opt for a solution that allows you, in the face of a possible and necessary migration, to maintain your authority and control over the data.

Technology must serve the business and its purpose, and this can only be achieved by building a Big Data architecture that is capable of responding to interdisciplinary teams and their needs. Big Data solutions like Cloudera are constantly evolving. Currently, they present an architecture that is capable of responding to the demand for data transformation information, of different forms of access or of different workloads, through environments that scale dynamically.

Having your own CPD, a multi-Cloud environment where availability, information security, multifunctional analysis, data governance and an open standard, which allows you to be the owner of your data and developments, is guaranteed, is an ideal option when it comes to identify appropriate Big Data providers.

Cloudera Data Platform works in Public Cloud environments, with a cost based on the use of resources, which is why it is a much more affordable gateway to Big Data for any type of use case, company or sector, than other options. . In addition, Cloudera has the requirements that every good service provider must meet and that we have been seeing in this post.

How can we help you from PUE?

If you are interested in exploring new solutions and technologies to innovate, improve, modernize or transform your business, we can help you. We are pioneers of Big Data. We have the expertise, a certified technical team and the recognition as Cloudera Platinum Partner, the highest category of the Cloudera partner program.

If what you need right now is train and certify your team in Big Datawe stand by your side to contribute to that purpose.

Contact

sales@pue.es for professional services in Big Data and Cloud

training@pue.es for official training in relevant technologies

exams@pue.es for official certification in related technologies

Links of interest

Big Data Experts

Big Data On-Premise vs. Big Data in the Cloud

Official Big Data training and certification with Cloudera

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