Nowadays, Data analytics is one of the well-known needs in organizations and something that has become essential, at least for “digital” companies.

There are a lot of business advantages with data analytics; however, to ensure that we can deliver useful insights on time, with quality, confidence and in a cost-effective way, the base layer, namely the infrastructure/provider, the tech stack, processes, and the approaches are very important points.

Assuming we already know the advantages of using cloud (if you don’t know yet, read this article), so, we have to decide which cloud provider we should use.

This decision is one of the most important ones. Cloud providers offer different kinds of services, so it’s necessary to perform an assessment to find the “best fit” provider according to our specific needs. This choice will impact the time, cost, complexity, and success of your Data Analytics Journey directly.

In this article, we will focus on some facts about using Google Cloud as a cloud provider for Data analytics projects.

Before getting into details on Google Cloud Platform(GCP), it is important to know the mission of the creator company: Google! Google’s mission is:

Having this in mind, we can easily understand that since the creation of google, their challenges have always been about Big Data. Google has dealt with all the main challenges of Big Data since its creation:

• Volume: How to address all the world information?
• Variety: How to address all the different sources?
• Velocity: How to process in time all the available information?
• Variability: How should the information be handled, considering that it can have many interpretations depending on the source and context?

So, how did Google solve it? How much has Google influenced the world of Big Data as we know it today?

Google has a long history of innovating in the data space and contributing to the Hadoop OSS echo system.

Even before the launch of the Google Cloud Platform in April 2008, Papers on GFS and MapReduce are widely credited with creating the first versions of Hadoop. Continued papers have resulted in projects such as HBase, Crunch, Drill, Beam, and TensorFlow. Google has been democratizing these internal technologies through GCP projects since 2011, starting with BigQuery.

Nowadays, Google has a wide range of products, all of them with a large number of users. Looking only for products with over 1 billion users, they have Android, Drive, Google Play, Chrome, Google Maps, YouTube, Gmail, Search and Google Photos. Another characteristic, something common in all of these products, is that all of these products run on the Google Cloud Platform.

All of these products process a lot of information, requiring smart analytics and AI functionalities. Some examples: Traffic suggestions on Maps, recommendations on Youtube, generated albums on Google photos, etc…

These facts show us daily that GCP is a powerful platform for addressing the complexity of data challenges.

Regarding data processing inside organizations, we can always find specific needs according to the organizations. For example, depending on which employee profile will interact with data, we can have business users, data analysts, data engineers, data scientists, machine learning engineers, and others… This results in different needs regarding the toolset to interact with data.

As a very mature company dealing with Data, Google offers a wide range of products envisioned to answer organizations’ different needs. The Smart Analytics suite is also widely integrated with the AI suite, Vertex AI.

The image below shows the diversity of services for each data lifecycle phase, the user profiles that could interact with these services, and the support and governance services, such as Dataplex.

In summary, we can conclude that Google Cloud Platform is a very powerful and stable platform, offering a wide range of Smart Analytics and AI services, with different options that can certainly address your organization’s custom needs.

If you would like to know more about Google Cloud or how Google Cloud Platform can address your organization’s custom needs, feel free to contact us.

BI4ALL has a Center of Excellence in GCP that can help you in your GCP data Journey.

Sources:

https://about.google/

https://services.google.com/fh/files/misc/dataprocessingorganisationwhitepaper.pdf