The amount of data and data sources is increasing enormously. Due to this increase, the urgency to manage all data from one location in the right way and to be able to use it efficiently. By applying data management within your organization, you ensure that data will work for your organization instead of the organization having to work for the right data.

1. Snowflake

The big advantage of Snowflake is that no complex infrastructure needs to be maintained. This is something that traditionally happens with data warehouse/data storage solutions. Of Snowflake you have access to a complete and secure data warehouse platform without the maintenance of it.

Snowflake is a cloud storage solution in the cloud where only the storage (storage) and computing power (compute) are paid. In addition, because it is located in the cloud, it is extremely scalable and various data warehouses/data marts can be set up. This makes it possible to distinguish well between combined data from different sources.

2. Azure Data Factory

Microsoft Azure Data Factory (ADF) is a data integration service in the cloud. Within ADF, data sources are visually merged through the more than 90 built-in and maintenance-free connectors. The big advantage of ADF is that it fits seamlessly with the other components that are part of the Microsoft landscape, such as Power BI. In addition, you can build ETL processes relatively easily without having to write huge amounts of code. Similar to Snowflake no complex infrastructure needs to be maintained by using ADF.

3. TimeXtender

TimeXtender is a powerful software platform used to set up a flexible data management platform. TimeXtender consists of 3 components: Operational Data Exchange (ODX), Modern Data Warehouse (MDW) and the semantic layer. You can easily connect all your raw data to the ODX by means of the more than 200 built-in CDATA connectors. This data can be stored in either a local database or an Azure Data Lake. You can easily build one or more data warehouses in the Modern Data Warehouse (MDW). In the semantic layer, the data model is built that can be easily transferred to both Power BI, Qlik or Tableau can be pushed. TimeXtender is fully integrated into the Microsoft landscape, so that it seamlessly connects to the Microsoft components Data Lake, Data Factory or Synapse. In addition, it is suitable for organizations that have a cloud strategy, hybrid work or manage everything locally. Finally, TX has a user-friendly interface within which the 3 environments (ODX, MDW, Semantics) can be displayed and managed without extensive programming knowledge.