We are your partner around Snowflake

With the Snowflake Data Cloud, you manage your data centrally in one place. We are happy to support and advise you on Snowflake.

Realize the full potential of your data - with the Snowflake Data Cloud

Cloud Data Warehouse

Snowflake is particularly suitable for the migration of a classic data warehouse to the cloud. As a specialized analytical database designed specifically for the cloud, Snowflake offers excellent performance, scalability and functionality especially in the analytical environment. Its dedicated development as a native cloud solution leverages benefits such as elasticity, transparent and usage-based costs, and high availability across regional boundaries directly from the underlying cloud environment (Azure, AWS, or Google).

Data Lakehouse

The demands on our analytical environments have been increasing for years. Not only is the amount of data growing rapidly, but the type of information required is also changing due to additional requirements from the business departments. While in the past mostly structured data from internal data sources was the basis of the analyses, today mostly semi-structured and unstructured data from numerous different sources, some of which cannot be verified, are also to be integrated. Snowflake offers a complete platform for all data types and enables transparent access to a wide variety of formats and sources. These can be structured virtually and can be analyzed transparently via classic SQL queries.

Marketplace for the data

Snowflake's comprehensive data sharing functionality also makes it suitable for implementing an architecture based on the principles of the data mesh concept. Each department manages its own data and ensures the security and governance of the information. Using the intelligent data sharing function, information can be transparently made available to other areas as so-called "data products". The data is not duplicated and stored redundantly, but rather defined as an accessible data view with appropriate security. The data is processed in the consuming area.

Determine needs based on past and future requirements.

Together with you, we collect ideas for future use in Data Warehouse / Big Data workshops, define the requirements and design a solution architecture.

Build a functional cloud DWH platform.

We design the platform for you, implement it and migrate your data from the existing data warehouse if required. We also help you with the connection and conversion of your other solutions such as ETL tools, BI front ends or self-developed applications. If desired, we implement an MVP (Minimum Viable Product) for you on this basis in order to get to know the new functionality and make the benefits transparent.

Modeling of a data lakehouse, data mesh or data fabric architecture

After the technical deployment, we move on to the business implementation. We model the future solution based on the appropriate architecture blueprints, taking into account your organizational requirements and our best practices.

Implementation of a modern, cloud-based overall solution

On this basis, we work with you to design the future data model, help design and create data integration processes, and support you in implementing meaningful dashboards, analyses, and standard reports. If required, we complement the solution with a comprehensive governance environment with central metadata, data catalog and data lineage functionality.

Ongoing monitoring of the project

Whether jointly developed in workshops, in coaching or as implementation partner; whether realization by you, us or third parties. We accompany you throughout the entire project lifecycle.

Get in touch with us

What is the Snowflake Data Cloud?

Snowflake is a cloud-based software-as-a-service provider that manages key data workloads in a complete platform. This includes data warehousing, data lakes, and data science, among others. As a "single source of truth", it brings together all data and data sources across the board and stores them in one cloud - the Snowflake Data Cloud

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  • Snowflake's Data Cloud breaks down the barriers of data isolation by enabling organizations to connect, share and leverage their data across and among each other. It allows organizations struggling to manage disparate infrastructure with heterogeneous data silos to focus on gaining insights from their entire data set.

Advantages of the Snowflake data plat form

  • Serverless Cloud Architecture
    Elasticity, transparent and usage-based costs, and high availability across regional boundaries are the benefits of this, leveraged directly from the underlying cloud environment (Azure, AWS or Google).

  • Separation of data storage and processing
    The data blocks of the tables are persisted in the object store of the respective cloud provider, while the processing of write and read operations takes place independently in so-called compute nodes. The separation of storage and compute nodes, any number of which can access the data simultaneously, opens up a wide range of possibilities, from intelligent workload management to dedicated allocation of resources and usage-based billing.

  • High-performance, scalable, analytical database.
    Snowflake is an analytical database whose architecture is a hybrid blend of traditional shared-disk and scalable shared-nothing database. Similar to shared-disk architectures, Snowflake uses a central data repository for persistent storage of data. The data blocks are intelligently partitioned and shared by all compute nodes in the platform. As a result, Snowflake provides excellent performance, scalability, and analytical functionality.

  • Different data formats
    Snowflake provides a data platform for a wide variety of data types from relational (classic databases) to semi-structured (XML, JSON, Avro, Parquet, etc.) to unstructured and allows transparent access to them. These can be virtually structured using Variant Data Type, File Format Definition and View Definitions and can be transparently analyzed using classic SQL queries.

  • Data Sharing
    All data stored in Snowflake can be transparently made available to other Snowflake users - even across company boundaries - via data sharing. Data that is to be shared is released accordingly and made available to other users worldwide, taking security and governance guidelines into account. The data is not duplicated and stored redundantly, but consumed via an accessible data view. The (read-only) processing of the data is carried out via the consumer's compute nodes, so that no performance impact or costs are incurred by the owner of the data as a result of the use of the data.

Feel free to contact us directly about Snowflake!

Marc Bastien
Software Architect TIMETOACT Software & Consulting GmbH
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Martin Clement
Teamleiter Analytics TIMETOACT Software & Consulting GmbH
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