A Cloud Data Warehouse is a database that is stored as a managed service in the cloud and optimized for scalable business intelligence and analysis. areto offers Cloud Data Warehouse architectures with Snowflake, SAP, Microsoft Azure, and IBM.
Cloud data warehouses allow companies to access the latest technology and infrastructure without incurring large upfront costs for technical equipment. They also eliminate the need for the time-consuming installation of hardware and software. Cloud data warehouses are generally made up of three layers: the server storage layer for storing data, the analytics engine layer for data analysis, and the front-end layer Interface for controlling and visualizing data. All the traditional functions of a data warehouse can be enjoyed in the cloud.
The cloud has become a natural integration point, as many corporate data are already generated from clouds. The (cloud) data warehouse follows this trend and is also implemented in the cloud. It is the foundation of your company-wide information strategy. Cloud data warehouses can process relational and non-relational data without conversion, allowing a consistent view of your source data and cross-analysis. The separation of storage and computing resources means that data loading does not affect performance, allowing data to be accessed almost live in the cloud data warehouse.
Many providers offer solutions that can be flexibly scaled up and down due to the cloud, to match the required workloads. This can be done without any disruption or maintenance breaks. In addition, pay-as-you-go models are offered, in which resources are billed according to usage and demand.
You can access your cloud data from anywhere, improving collaboration between different project teams through web-based interfaces. At the same time, cloud data warehouse providers ensure the compliance of guidelines and high security standards, including role-based access controls and auditing tools. Automated backups and disaster recovery also protect against data loss.
Many cloud data warehouses offer SQL support for popular data analytics, business intelligence tools, and ETL. In-memory caching and parallel query processing also ensure high performance. This allows you to optimize your data usage and make informed decisions.
Pay-as-you-go payment model
Nearly unlimited scalability
Compliance and security features
Location-independent data access
Separation of storage computing
Improved collaboration of data teams
Based on your individual requirements, we will see how much you can save and how much performance you can gain.
The Snowflake data cloud platform offers a wide range of solutions for processing your data. It is a global network in which you can mobilize your data to an almost unlimited extent. You can use any cloud, such as AWS, Google Cloud Platform, or Microsoft Azure. The multi-cluster environment in the Service Layer allows you to run various workloads or have the clusters automatically scale.
The architecture allows you to run multiple workloads from different teams while maximizing performance and complying with guidelines. The Snowflake Data Cloud Platform supports comprehensive data integration, data science, and business intelligence with SQL support, so you can focus on the value of your data.
Further information on Snowflake Data Cloud.
SAP Data Warehouse Cloud simplifies data integration and brings together pre-integrated databases, data management and analysis functions in a cloud solution to accelerate business results. This is based on the SAP HANA cloud database and enables in-memory data processing, analysis, and data virtualization functions.
SAP Data Warehouse Cloud allows you to use data from SAP and third-party clouds and on-premises environments and process it in real-time at in-memory speed. This eliminates data silos and provides your business users with self-service access to data and analysis. You minimize the complexity of your architecture solution, creating value for your company and IT. You only pay for the actual use of data and performance.
Further information on SAP Data Warehouse Cloud.
Microsoft Azure Synapse Analytics is Microsoft’s cloud data warehouse solution. It is an integrated business analysis service for faster insights from data warehouses and big data systems. Azure Synapse Analytics offers almost unlimited scalability, all applications in a unified interface, and unparalleled security through the most advanced data protection features and dynamic data masking. Integrate your data without code through 95 native connectors. You also have the opportunity to accelerate your AI and BI projects through integrated tools such as Power BI, Azure Machine Learning, and Azure Cognitive Services.
Azure Synapse Analytics includes Apache Spark and SQL engines, as well as support for your preferred language (T-SQL, Python, Scala, Spark SQL, .NET). Benefit from predictable performance and therefore predictable costs with high performance.
Read more about Azure Synapse Analytics here.
IBM Db2 Warehouse on Cloud provides independent scaling of compute and data storage. It can be flexibly adapted to your individual requirements via the DB2 Warehouse on Cloud web console or API. You can easily increase compute power at peak demand and reduce it when demand decreases. This allows you to reduce costs without sacrificing performance. You also benefit from adaptive workload management, which automatically manages resources between competing workloads.
Your daily operations, including database monitoring and failover, are fully automated and complemented by a ready DevOps team. IBM Db2 Warehouse on Cloud also gives you built-in AI and ML capabilities that you can train and run directly in the database engine. Connect your IBM Cloud or AWS platform to IBM Db2 Warehouse on Cloud and unlock the full potential of your data.
Learn more about IBM Db2 Warehouse Cloud.
To fully utilize your cloud data warehouse, integration and transformation from the various data sources is essential. Use data connectors to easily and with high performance load your complex data into your cloud data warehouse, considering your individual infrastructure and security requirements. Through aretos best practice approach and years of experience, we offer the solution that best fits your company.
Matillion offers powerful solutions for data transformation and integration into cloud data warehouses with the products Matillion Data Loader and the cloud native tool Matillion ETL. Data transformation for Snowflake, Microsoft Azure, Amazon Redshift, and Google BigQuery is supported. Matillion ETL can be natively integrated and transforms your business data in the cloud data warehouse for deeper insights and analysis. Matillion can be customized to fit your individual infrastructure and security requirements.
With Matillion ETL, you can set up data pipelines in minutes to data platforms. Take advantage of the Matillion cloud strategy with many cloud connectors to social media platforms, databases like SAP and Excel, and many more.
Matillion ETL for Snowflake has been developed to help you get the most out of your Snowflake cloud data warehouse. You can easily migrate your data with a few clicks through more than 70 pre-made data source connectors. The universal REST API of Matillion allows you to connect to any API-enabled application and automate the loading of your data through job scheduling. This guarantees faster access to data for business intelligence, reporting, and visualization. Take advantage of the full performance of the cloud with powerful transformation and get Matillion ETL for Snowflake through the AWS, Azure, or Google Cloud Platform marketplace.
dbt is an open-source tool that allows your data analysts to transform data by writing SQL statements. The SQL-first transformation workflow acts as an orchestration layer in your cloud data warehouse. This layer allows your data teams to work directly in the warehouse with trusted datasets for reporting, machine learning modeling, and workflows and deliver them along with documented code. Calculations are performed at the database level, making the integration process fast and secure.
All your employees with SQL skills can now use dbt to create production-ready data pipelines. Use dbt and turn your data analysts into data engineers! Especially with big data, this ability is of great importance. The data warehouse cloud platforms of Snowflake, Google BigQuery, Databricks, AlloyDB and AWS Redshift are supported.
Get dbt now and take the next step in your data journey!
Further information on Datavault Builder.
Datavault Builder is developed to reduce complexity in data migration and support the implementation of agile cloud data warehouse architecture. Data migration is not just about copying data, but rather a continuous process allowing data to be analyzed and processed in real time. Within your database, Datavault Builder creates a Data Vault architecture including ETL/ELT processes, which allows multiple data teams from different departments to work simultaneously. All data sources with Java Database Connectivity (JDBC) are supported, such as Microsoft SQL, Excel, Oracle, IBM DB2, TeraData, and Hadoop Hive.
With Datavault Builder, you can quickly respond to changes, have full auditability and historization of your data, and additional automatic documentation. Utilize Snowflake and Datavault builder to maximize the efficiency of your cloud data warehouse.
Wherescape® provides an integrated development environment for the creation, deployment, management, and renewal of cloud data warehouses and big data solutions. Native database objects are created, optimized for Microsoft SQL, IBM Db2, Snowflake, SAP, Exasol, Oracle, and many more. This allows you to access source data from various environments, create procedural code, scripts, and tables. You can streamline workflows and achieve faster deployment of your data. The environment is also reliably documented, making maintenance and adjustments to changed requirements easier to perform.
Wherescape® also supports the automation of your cloud data warehouse.
Further information on Wherescape®.
Cloud data warehouse automation tools (DWA) are metadata-controlled and help you streamline the management of your cloud data warehouse. They take over the continuous integration and deployment of data and manual writing of code. Tedious and recurring tasks such as source identification, dimension assignment, and change analysis can be automated to increase the productivity and agility of your cloud data warehouse. They cover the entire lifecycle of your cloud data warehouse solution.
From analysis, implementation, documentation, to monitoring and maintenance. Using best practices, the tools deliver high-quality code and are easy to use with graphical user interfaces with point-and-click. By using cloud data warehouse automation tools and the expertise of areto, you can reduce the time to value and optimize the cost of your cloud data warehouse. Use the tools of VaultSpeed, Wherescape, Matillion, Datavault Builder and areto Data Chef with areto.
Getränke Hoffmann is one of the most successful beverage retailers in Germany, with over 500 beverage specialty stores nationwide. There was a pressing need to find a new and sustainable BI architecture solution that could meet current challenges, increase efficiency, and be flexible and scalable. With areto, Snowflake Data Cloud was found and implemented as a solution, serving as an interface to combine the benefits of various providers. Data can be integrated using Wherescape® transformation engines. In addition, repetitive patterns and processes can be recognized and automated accordingly.
Getränke Hoffmann uses Power BI for analysis and visualization. Snowflake Data Cloud provides the foundation for integrating additional tools and analyses in the future to promote innovation within the company. The solution found can be scaled agilely and flexibly by the Getränke Hoffmann team to meet the needs of growth and new challenges.
The Duisport Group is a subsidiary of Duisburger Hafen AG, which is the owner and operator of the world’s largest inland port. Due to the high volume of several million containers handled annually and the networking with many logistics partners, large amounts of data must be stored, analyzed, and ultimately used for informed business decisions.
areto’s task was to implement the cloud migration from the existing BI landscape, which was used on-premises, to the Microsoft Azure Cloud. To do this, the requirements of Duisport for the cloud architecture were recorded in various workshops. The customer’s requirements for scalability, data integration, and flexibility had to be met by the new architecture. The modern Azure Data Platform offers exactly these benefits and, in combination with the Power BI cloud service, opens the way to self-service BI at Duisport.
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