Data warehouse
A data warehouse is home for all your data.
Combine data from all your important information systems into one place where it's easy to access and utilize. Using a data warehouse makes business analytics, forecasting and planning easier and more efficient.
Building an efficiently working data warehouse is routine for QuickBI experts. With more than 300 integrations, we combine all the data you need from your company's various systems to your data warehouse and your BI system.
Agile BI reporting and data analytics
By integrating all of your data into a data warehouse, you can automate parts of your reporting process, and you also get a great tool for testing your data and creating and quickly verifying new data models and analyzes.
Centralized data is easy to utilize
We gather all the data sources needed for your reports and analytics into a data warehouse. The data is formatted to be easy to use with the BI tools you choose, and system integrations are configured to update everything automatically.
Much more than just a data warehouse
Data warehousing is an integral part of fast, reliable and comprehensive reporting. QuickBI can build a seamless, efficient reporting and analytics system for your business, where all data flows effortlessly and securely from source systems to the data warehouse and further to the BI tool of your choice.
Deployment and maintenance of the data warehouse
QuickBI can help you get started with the Google BigQuery data warehouse. If you wish, we can also take care of maintaining it in the future.
BigQuery, part of Google's cloud services, is a highly scalable data warehouse for businesses of all sizes. It is not too robust a tool to take advantage of relatively small amounts of data, but it also works well with considerable amounts of data.
BigQuery is a scalable and cost-effective solution also in terms of pricing, as it is based on the use of the product and services. The price depends on the number of analytics processes and the storage space required.
BigQuery is an excellent basis for reporting and machine learning models. The data in the data warehouse can be processed and analyzed with the desired BI tool. As a service provided by Google, BigQuery is also a good option if the company wants to keep its cloud data within the borders of Finland.
QuickBI can also implement integrations with other data warehouses (e.g. Amazon Redshift / AWS Redshift, Azure Synapse, Snowflake).
Why join data while it is in the data warehouse?
More information available and a reduced amount of manual work needed
- More accurate cashflow forecasts
- Being able to forecast financial key figures by utilizing data collected from f. ex. sales and / or production related information systems / software
- Planning a budget
- Monitoring the planned budget
- Compiling billing material
- Automatic salary data collection
- Automatic accounting voucher data collection
More diversified reporting through utilization of several data pipelines
- Monitoring sales profitability
- Activity reporting
- Monitoring efficiency of salespeople
- Sales pipeline reporting and forecasting
- Calculation of customer life cycle value
- Related expense tracking
- Reclamation reporting
- Customer satisfaction
Data from different systems and software to be used for marketing purposes
- Customer segmentation based on purchasing behavior
- Identification of established and profitable customer segments
- Calculating the cost for customer acquisition between different marketing channels
- Customer purchasing behavior reporting based on where or through which channel the lead was acquired from
- Timing marketing campaigns based on seasonal variation
It is possible to make the work of human resources easier by collecting data from different sources. For example:
- Organizing available human resources according to a production plan
- Monitoring the live implementation of a working hours budget. For example, a frequently updatable view of a working hours actualized vs budget by month.
- Monitoring the ratio of billable work in relation to total working time
- An automatically updated "presence" calendar along with calculation of daily resources, taking into account holidays, sick leave, trips, training days, etc.
Comprehensive reporting enables improving the efficiency of production
- Reducing production material losses with better visibility towards ensuring that the materials are used before they go bad / turn sour
- Comparison of component inventory levels to an existing production plan. Monitoring the inventory levels of critical components
- Monitoring work efficiency, for example between different production lines and / or products
- Material loss monitoring and analysis
- Comparison of planned and actual profit margins
- Calculation of activity based costs. For example, linking the costs of logistics, management and sourcing on existing products
A better understanding of customer service can be gained by combining data from multiple sources
- Tracking the ratio of deferred / cancelled customer appointments by customer service representative
- Proper allocation of resources according to level of busyness and time of day
- Response time monitoring
- Monitoring service ticket queue status / situation
- Customer satisfaction
Surely by now you are convinced that a data warehouse is by far the most efficient way to manage data? Contact us and we'll talk more.