Excellent prospects with
data analytics from the cloud

In the digital age, data is the new gold. The ability to find, process and refine vast amounts of data and thereby gain new insights is part of Google’s and Wabion’s DNA. We will show you how to increase the value of data, reach customers better and tap into new business areas with Google Cloud Platform (GCP) .

Big data into the cloud

Whether small or big data, the digitalisation of business processes carries with it exponential data growth. Companies with an on-prem IT infrastructure often find themselves unable to cope with the increase in data volume and reach their limits when analysing said data. Wabion can help overcome these limitations by developing solutions that allow you to realise the full potential of your IT infrastructure and your data.

Challenges for on-prem solutions in the age of big data

Expansions are lengthy and pricy

More data requires more storage and computing power. Expanding on-prem capacities costs more and takes longer than on GCP.

Database maintenance expenditure

Companies with on-prem infrastructures require more staff capacity. An increase in data analytics with the same capacities increases expenditure even further.

No solution for diverse formats

Data formats for specific systems (e.g. ERP) make comprehensive on-prem analyses more difficult. GCP offers diverse options for multi-format analyses.

Infrastructure often remains unused

Data analytics require ad-hoc computing power. On-prem infrastructures often remain unused. ‘Per-per-use’ solutions on GCP eliminate this issue.

On-demand solutions
for your data with Google Cloud

To keep up with data analysis trends, companies are increasingly turning to cloud solutions. As the leading public cloud provider when it comes to data analytics and AI/machine learning, Google Cloud covers all needs concerning the storage, preparation and analysis of central business data:

As illustrated in the big data process model, Google Cloud covers everything from databases to predictive analytics to ensure that you get the most out of your business data:

  • Data ingestion: With Cloud IoT for peripherals, Cloud Pub/Sub as frequently employed middleware and the object-oriented storage solution Cloud Storage, Google Cloud provides efficient solutions for several different use cases.
  • Data transformation: Chiefly responsible for the T in ETL process (extract, transform, load), Google Cloud Dataflow and Cloud Dataproc play a central role in automated, scalable and cost-efficient data analysis. For businesses that rely on Hadoop, Spark or similar solutions, Cloud Dataproc is a valid ‘pay-per-use’ alternative to on-prem; you only pay for ad-hoc use of the required data analytics resources.
  • Databases: Based on your individual needs, you have either relational databases, such as Cloud SQL and Cloud Spanner, or NoSQL databases, such as  Cloud Bigtable and Cloud Firestore, at your disposal.

As is always the case with Google Cloud, individual products are easy to combine. Wabion has, for example, developed a data analytics platform for AXA — Switzerland’s leading insurance provider — which combines  Cloud Pub/SubCloud StorageDataflow and BigQuery while at the same time meeting all compliance requirements needed in such a tightly regulated environment. 

Data Analytics & business intelligence

BigQuery illustrates the power of the Google Cloud Platform (GCP) when it comes to data analytics. Combined with other GCP tools like Cloud Storage, Cloud Pub/Sub or Cloud Dataflow for automated ETL and data integration processes, the ‘serverless data warehouse’ serves as a central hub for extensive data analyses with uniform data formats (structured, semi-structured) originating from a variety of data sources. 

With BigQuery, the borders between data lakes, data warehouses and data marts get blurred. Big data becomes big value, and you get to benefit in a number of ways:

No-Ops: Fully managed servers (serverless)

As with most GCP data analytics tools, you concentrate on your own data and insights while using BigQuery. Scaling, maintenance, etc. are automated.

Speed & power thanks to Google’s infrastructure

Whereas on-prem big data analytics often requires a lot of time, you benefit from the basically unlimited computing power which Google Cloud provides.

Many sources, one data lake

The right combination of GCP tools bundles data from a variety of systems and formats under a single roof and/or a central analysis which can be complemented with machine learning tools.

Pay per use only

When it comes to data analysis with Google Cloud, you only pay when and for what you use. ‘Ad-hoc’ infrastructure eliminates the costs associated with unused resources.

In addition to its technical advantages, BigQuery also impresses with its user-friendliness. All relevant persons can receive access to the insights gained according to your GCP access rules (Cloud Foundation). 

Looker can also be easily integrated into BigQuery and other GCP tools and, as an end-to-end solution, allows for new possibilities when it comes to data visualisation. Take advantage of Wabion’s expertise and learn how you can use GCP data analytics, AI and machine learning to optimize your business processes.

Data Analytics ist die Basis für effiziente Business Intelligence


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Artificial Intelligence (AI) And Machine Learning (ML)

AI and ML can play a crucial role both before as well as after comprehensive data analysis. AI and ML are proven tools when it comes to unifying different data formats and making unstructured data accessible for data analytics. With the help of APIs, GCP products such as BigQuery or Dataflow can be enhanced with additional AI and ML functionalities. These include:

  • BigQueryML as ML-Libraries directly integrated in the Data Warehouse
  • Vision AI for interpreting and categorising image and document data
  • Video AI uses ML to recognise and classify video material
  • Cloud Natural Language und Document AI for sentiment analysis and interpreting unstructured texts
  • Cloud Translation for language recognition and translation

GCP products for AI and ML are usually available in both predefined and customisable versions.TensorFlow as a framework for programming and AI Platform for training, hosting and administering ML models are two further central building blocks of Google Cloud’s wide-ranging AI and ML offer — for example, for predictive analysis based on data queries with tools such as BigQuery.  

The data and AI/ML experts at Wabion will not only consult your firm when it comes to AI and ML, but will also develop and implement models that are enhanced with artificial intelligence and are custom-tailored to your business processes.

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