How Cloud Analytics Changes Big Data

Living in the age of Big Data is a challenge for all big companies. Most of the time the existing in-house infrastructure isn’t entirely fit to deal with the sheer amount of customer data that has to be processed. Saving and analyzing that much data is costly and requires an enormous amount of resources that many companies aren’t able to efficiently supply.

Our Solution

The rising importance of this issue is the reason we decided to form a partnership with Databricks to provide our clients with a zero-management cloud platform that is built around the well-known unified framework Apache Spark. Through this partnership, we are able to offer our clients the simple implementation of cloud-based unified analytics stack.

This unified approach gives you the opportunity to focus on what’s important – your customer data – while at the same time reducing the need for complex in-house infrastructure and, of course, unnecessary operating costs. This is possible through the fully managed, scalable and fast cloud-infrastructure that Databricks provides.

Why the Cloud?

It is a well-known fact, that key figures that are based on analytical methods can effectively be used in your marketing strategies. Using the results from these analytical models in your customer communication, e.g. for the calculation of Next Best Offers, not only improves customer satisfaction and response but also, most importantly, your company revenues.

With Databricks all stages of data analytics – from complex ETL pipelines to experimentation and the provision of ML-applications – can be handled in a resource-efficient way in the cloud. That way companies are able to focus on the key figures that are immediate to their success and don’t have to deal with the headaches of clunky and complicated tools and difficult in-house infrastructures. This increases the flexibility and scalability and, at the same time, saves IT costs and time efforts.

How Does it Work?

Databricks simplifies Big Data and AI with a unified platform approach where Data Engineers and Data Scientists work closely together on one platform. This enables teams to work more efficiently on Big Data and AI projects and utilize the power of Apache Spark.

The development interface based on notebooks is providing a collaborative workspace where teams are able to work closely together. The Databricks cloud also provides a simple interface for easy workflow and job management, which enables teams to put data pipelines and ML models more efficiently into production.

But is it Safe?

As the topic of data security and privacy laws troubles firms of all sizes and industries, it is important to emphasize the security aspect of cloud-based solutions. The methods aren’t new and are already in use by big-name companies like Apple, Netflix, Pinterest and Instagram.

Cloud-based data analytics are the drivers of innovation as they are characterized by flexibility and fast communication processes. Handling the challenge of adhering to data privacy regulations while at the same time getting the most out of sensitive customer data is a delicate process that Databricks has diligently subscribed to. From encryption and identity management to access controls and detailed architecture documentation, every layer of the Databricks Unified Analytics Platform is built to provide the most advanced protection of your customer data. That way the entire user experience is centered around accelerating innovation while at the same minimizing risk.

We are excited about the partnership with Databricks and the benefits we can now offer to our clients.

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