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Do you have a data strategy?

An enterprise data strategy is a comprehensive plan that outlines how an organization will manage, utilize, and govern its data to achieve its business objectives. This strategy serves as a roadmap for data acquisition, storage, analysis, and security, ensuring that data is treated as a valuable asset. By aligning data initiatives with business goals, an enterprise data strategy empowers companies to make informed decisions, optimize operations, and drive innovation.

More interested in actual technologgy?
EXplore Snowflake

Key Goals of a data strategy

Identify Data Sources
What data does your company have? The first achievement to a successful data strategy os the identification all data sources within your company including data that is not stored within your systems but may be stored in third-party applications.
Make Data Accessible
The true value of data hides in its relationships. Therefore you have to make your data accessible in a way that allows all departments to gather data in a single source of truth.
Structure your data
Many data driven systems use different representations for the same fact. A data warehouse structures data into logical blocks of the same format.
Turn Data into Value
It is the insights derived from the data and its relationships that provide the true value. The structured data is the foundation for data analyics, reporting, and forecasting.
Act upon data
Once you have the insights, the ultimate goal is to derive action from your data, or the insights generated from that data.
Rooted in the core of your business, your data, automation is the key to efficiency, precision, cost reduction and speed.

What is snowflake?

Part of the Visualization of the Snowflake Layer Architecture, showing the Optimized Storage Layer.Part of the Visualization of the Snowflake Layer Architecture, showing the Elastic Multi-Cluster Compute LayerPart of the Visualization of the Snowflake Layer Architecture, showing the several virtual Warehouses.Part of the Visualization of the Snowflake Layer Architecture, showing the Cloud Services Layer.Part of the Visualization of the Snowflake Layer Architecture, showing the SnowGrid and SnowPark Layer

Optimized Storage

Snowflakes optimized storage layer that is 100% decoupled from the compute layer is a key reason for Snowflakes speed and flexibility. Adding Snowflakes proprietary table format you get:
> Built-in Encryption
> Built-in Compression
> Superiorquery performance

Elastic Multi-Cluster Compute

The compute architecture of Snowflakes is built to maximize performance and flexibility of your analytical workloads. A single engine that can be scaled up and out offering a seamless and throughout compute cluster independant of your favourite language.
Near Unlimited Compute Power
The fast your analytical workloads run, the fast they deliever answers to your questions. The near unlimited computer resources of Snowflake deliver answers faster than you can ask the questions.
Sale Up and Down in Seconds
Snowflake does not require intensive resource planning since compute can be scaled up and down in a matter of seconds.
Per Second Billing
Per second billing combined with almost zero coldstart delays allows fine grained cost management keeping your data warehouse costs fair and low.
Choose your Language
Every data science team has their favourite tech stack, and Snowflake values that! Choose your favourite language from Python, SQL, Java or Scala.


Warehouses are the compute unit s that run your worklods. The separation of workloads into distinguished warehouses allows you to separate e.g. production, development, and data loading workloads. This ensures that your production workloads always deliver peek performance even when running challenging development pipelines.
You are in control when it comes to sizing your workloads. Offering 10 warehouse sizes you are in full control of performance and costs at the same time.

Cloud ServiceS

The cloud services tier in Snowflake is an ensemble of services that orchestrate actions across the platform. It seamlessly integrates various Snowflake components to handle user demands, ranging from logins to dispatching queries. Additionally, this layer operates on compute resources provided by the cloud provider through Snowflake.
> Authentication & Access Control
> Query Optimization
> Infrastructure Management
> Meta-Data Management

Snow Grid, Snow Park, ...

Snowflake is not just a data warehouse technology with ultra fast query performance, near unlimited storage capacity, and flexible compute options. Snowflake is a platform for developing applications, sharing data and performing data science.
Snow Grid
Interconnect your business’ ecosystems across regions and clouds with a cross-cloud technology layer that lets you operate at global scale.
Snow Park
Snowpark is the answer to the question how you run data science workloads when using Snowflake. More specifically, you run them next to your data, directly in Snowflake. Using the DataFrame API of Snowflake, you get Pandas like access to your enterprise data.
Container Services
Ever heard about Large Language Models like GPT oder Llama 2 that multiply each and every business? With the announcement of our partners NVIDIA and Snowflake, you can run Generative AI application directly within Snowflake, leveraging the GPU compute capabilities of Azure, AWS, and Google Cloud.

Reach out and learn more!

Learn about Snowflake in a live demo and clarify all your questions with our experts! As a certified Snowflake Partner, we offer everything from initial setup to complete implementation and support.
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