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When companies contemplate carrying out a digital transformation by implementing new Big Data technology and Data Centric models, they face a variety of challenges that require planning, defining objectives, decision making and assessing results.

In this post, we are going to explain how this process unfolds with a success story: the story of one of the most important multi-national insurers in the country, Caser. 

Caser is an insurance and services company that has been operating in Spain since 1942. Their offering includes health insurance, health and medical care centers, dental clinics, maintenance and support services, and a network of financial agents. The group currently has a staff of more than 6,700 people.


Caser already had a model that was designed to be data centric, with a main core based in a Data Warehouse, but they needed to improve certain aspects and add new capabilities. 

Their objective was to improve aspects such as scalability and security in massive processes. Additionally, they were interested in adding new capabilities in relation to data governance, lineage, cataloging, access controls and auditing. 

The aim was to build a self-service, analytical BI platform, where the user could find the widest variety of information as quickly as possible, in the best, fastest manner. They needed to become more agile

Hugo González, Head of the Information structures and advanced Analytics Area at Caser, spoke to us about all this in the interview that he gave us recently.

“The challenge for us is to start having a platform available that not only has the data and can provide it, but that does so much faster and in a more agile manner, and for the data to be as accessible as possible throughout the company. Data is a key asset,” asserts Hugo González, “especially in a financial company like ours. Facilitating access to data, facilitating the incorporation of new information, which can be exploited in any context in the simplest possible way is a challenge, but that is what we are looking for.” 

If you want to know more, we recommend you check out the full interview:


First decision: which platform to choose

Caser analyzed different technologies, and assessed the various options and platforms available on the market. They decided to choose Big Data technology and, more specifically, a Big Data cluster with Cloudera

During the process of digital transformation at the insurance company, their choice of Big Data enhanced the data centric model from a single open platform, Cloudera, where you can get everything you need in a managed, administrated manner.

First steps towards implementation of Big Data with Cloudera

A data strategy like the one Caser implemented requires a roadmap for the next few years. 

In their case, the first step was to design and implement a Data Lake, in order to begin to save the information. They substituted the Staging Area Data Warehouse for a Data Lake in Cloudera. In practical terms, this means that they substituted the relational database and implemented a Data Lake in Cloudera. 

In this context, they used technologies like Apache Impala, Apache Kudu and Apache Spark. Impala for performance, Kudu for the need to modify data and Spark to recode the SQL at scale. 

They also chose to maintain technologies that they had been using for years, in order to make the most of the knowledge and experience they had accumulated, such as the ETL tool. With this decision, they were able to minimize risks and meet their objectives within the planned time frame.

Successful results 

One of Caser’s objectives in this transformation process was to make this move, to a technology that is totally different from the one they used to have, transparent for the business, for users and for processes. In this sense, it was a complete success.  

Another of the objectives they were able to achieve with Data Lake was to centralize the data in a single site, make it usable for reporting and analysis, and even integrate it into production applications with rest api, being able to get data in real time for fraud detection.

Collaboration between PUE and Caser

We have formed a team with PUE, and each party has got the best out of it. We have got the knowledge of Cesar’s data. They have got knowledge and experience in technology.

asserts Hugo González, in reference to the collaboration with PUE

PUE has collaborated with Caser from the initial phase of the digital transformation process in substituting the Staging Area Data Warehouse for a Data Lake with Cloudera. They have participated throughout the project, providing technological solutions, from how to get the ETL tool to connect to the data lake more quickly and efficiently, to the design and changing of all processes. They designed and implemented a data architecture that is capable of improving the load performance of the Data Lake, enabling more efficient data analysis in less time:

  • Processes of conversion of traditional programming languages, such as PL/SQL, to Spark processes with Scala, reducing data analysis process times from hours to minutes, allowing them to be more agile and have a business diagnosis in almost real time.
  • Cluster configuration and security policies.
  • Integration of PowerCenter processes into the Cloudera Platform.

It has now begun a second phase in the collaboration, with one of the company’s most massive processes.

PUE’s expertise in Big Data is noteworthy, but also its commitment and collaboration.

Hugo González.

If your company is contemplating a modernization and transformation process and needs to get started, we would be delighted to analyze your specific case in order to advise you on the solutions and technologies that would be most suitable for your project.

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