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Data processes such as constructing a data warehouse are complex and require a lot of data to be managed.
To set about that efficiently and in a structured manner, it is best to integrate everything via a modern data platform in a data store.
Modernizing your data landscape also means combining the more traditional approach to data warehousing with a more agile approach for data process integration.
Now, more than ever, data visualizations need a solid and robust foundation of structured data elements referred to as facts and dimensions, with which Power BI can connect to the reliable data to create up-to-date comprehensive and meaningful reports.
On the other hand, business leaders need faster insights to respond to rapidly changing markets. Rapid and effective decisions are needed that are based on compiled data.
The implementation of structural data changes and data visualisation evolutions are subject to an increased frequency. The time-to-market for this must be prolonged as much as possible.
With the addition of new tools, such as Microsoft Azure Synapse Analytics, we can combine the best of both worlds.
We still have pipelines orchestrating data processes that are used for data warehouse loadings in batch-oriented approaches, and we have direct connectivity to data stored in files on Azure storage, which allow us to generate insights in close to real-time.
With Synapse pipelines – identical to the standalone Azure Data Factory – you can utilise and process data from many different sources, including IOT sources, in your data archive, DataMarts and data warehouse.
The end point is a Power BI integration into the SaaS Synapse Analytics suite, so you can easily check and verify your reports even before they are published on your corporate reporting portal.
What’s more, you can easily run data science exercises on your data or even produce machine learning models.
Everything is integrated and adaptable.
A data archive is designed to integrate data from multiple sources for additional operations on the data.
Irrespective of whether your data comes from an IOT device or from your traditional ERP and CRM systems, we combine the data and make them available for use.
It is a complementary element to a data landscape and can be used for operational reporting, controls and decision-making.
It gives you the ability to maintain a history of all your data. This means you can feed your data warehouse data from a period in the past. A data store goes way beyond that. Not only can you apply data quality rules and scores to incoming and outgoing data traffic, but also apply data cleansing rules. In this way, you will have enriched and supplemented your data into high-quality, standardised data that increases the accuracy and quality of your data visualisation and reporting requirements.
A data store provides more opportunities for various kinds of users: advanced, expert, key or power users who can quickly create insights, support and function detection for business and IT departments. It can also be used as a source for your data science-related activities or data hub activities.
Would you like to know about the power of a modern data platform combined with a modern data warehouse?
We can help you on your way with a five-day analysis and POC. We will examine your source systems so that we have a clear view of the organisation of the data store and data warehouse. The next step involves us establishing a BI roadmap based on your business requirements, so that your company can maximise the benefits of a modern data warehouse combined with a data store.
5,990 EUR (excl. VAT) for 5 days of analysis and POC.
Kohera offers solutions to quickly and easily connect to these information sources and thus achieve faster business processes and better insights.