Cloud analytics lets you process huge amounts of data more effectively and some makes certain analytics use cases possible. Support the selection process of the right cloud provider from the AWS and AZURE portfolio.
We consult on suitable cloud analytics tools and make recommendations based on your cloud strategy at various levels of abstraction as Infrastructure as a Service (IaaS), Platform as a Service (PaaS) and Software as a Service (SaaS) and serverless implementations.
We automate your infrastructure so you can focus on the most important aspects of your business. With Cloud analytics, your organization is no longer tied to limited, pre-installed analytics tools.
As part of Cloud BI, we support the selection of suitable BI tools such as DWH, reporting and planning solutions in the cloud and the implementation of your BI projects with cloud technologies.
As part of the selection process for cloud data engineering we evaluate suitable data integration tools such as Classic ETL tools (SSIS, Informatica, etc.), modern ELT tools (Databricks, Hive, NiFi, etc.) as well as data lake components (ADLS, S3, Blob Storage, etc.)
For Cloud data science we can accordingly support the technology selection and implementation of suitable data science tools and every other aspect of your data science projects in the cloud.
That's what we offer
Professional Consulting and implementation for
- Cloud BI
- Cloud data lake
- Cloud data engineering
- Cloud data science
Our consulting services include all cloud analytics tools, including Databricks, HDInsight, Azure Data Lake Analytics, Azure Studio for Machine Learning, Amazon Athena, Amazon EMR, Amazon Redshift, Google BigQuery and Google Cloud Dataproc as well as other solutions.