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Most powerful knowledge management solutions

Solu Digital provides knowledge management and analysis models for today’s complex businesses.

A well-built data warehouse is half-done knowledge management


Business information is constantly utilized more and more versatile to support the implementation of the strategy and to increase the efficiency of day-to-day operations. A well-implemented Data Warehouse (DW) plays a key role in the foundation of modern Business Intelligence (BI) systems that visualize data collected from a variety of sources for the management and analysis of business information. 

The functionality of the knowledge management solution model must be considered from the point of view of the whole context. That starts with the strategic parts of the organisation working with the processed information from reports and tools. A functional solution for BI reporting is built at both the technical and business level based on the features and functionalities defined jointly by the representatives of the different areas of the organisation. 

It should be remembered that successful knowledge management also requires processes that have been tested and documented to support the development of the operating culture and the implementation of the BI system. 

The pain of traditional data storage  

Before, implementing traditional data storage was one hell of a thing; it was expensive and slow. The physical costs of traditional development, testing, and production environments, as well as on-premises solutions spanning 2-3 SQL servers, were in a class completely of their own. In the first projects, it could take as much as a year from the initial definition to production. 

In the past, data warehousing projects could take time from multiple parts of an organization many times compared to modern data warehousing practices. The development and maintenance of a data warehouse-based analytics and reporting system consisted of many manual work steps, such as extensive, step-by-step definition work and the implementation of data models and flows. 

Many of these manual steps resulted in higher costs in relation to the added value they produced. Fortunately, modern data warehousing projects are no longer eternity projects that consume in a months’ worth of time and six-figure sums of budget to get something done. 

Automation brings speed and efficiency to information management 

Today, multiple manual work steps can be automated and streamlined to a great extent, resulting in faster realization of benefits by reducing manual implementation. Automation can enhance data discovery, collection, management, and utilization. 

Data warehouse, which is built directly to the cloud database with cloud data download tools, is efficient and straightforward, and especially cost effective. Microsoft provides comprehensive tools for the various stages of data warehouse implementation. 

For example, raw data can be easily downloaded from source systems directly to the Azure Datalake service and from there to the actual data warehouse using the Azure Data Factory service. In this case, the source systems do not have to be loaded with, for example, additional conversion queries or tables. Utilizing the data warehouse makes it easier to build the actual reporting data model using Power BI or Azure Analysis Service. Reports, on the other hand, are most typically made using either Power BI Desktop, Microsoft Excel or Power BI Report Builder. 

Industry-specific solutions for different needs 

With very little effort, automated steps can reap great benefits to organizations in a variety of industries, such as an organization in the food and catering industry, where manual work on data conversion and calculation took up to several days. Today, data is read through interfaces into a data warehouse, where it is prepared for dimensions containing ready-made structures, for example according to cost centers. When calculation formulas, etc. are made in the Microsoft Power BI model, the data can be utilized for reporting quickly, and a significant amount of time required for the process can be saved. 

In another customer case, with an organization operating in the real estate industry which uses several different enterprise resource planning (ERP) systems, the data update interval dropped from once a day to 20 minutes, and the reports worked significantly faster. Today, our collaboration covers all areas of reporting, entire data warehousing, and various experiments with new technologies. 

The controller of another real estate operator spent a large portion of his working time manually collecting data and calculating by cost center or region. Financial figures and customer satisfaction data from different systems were combined into a single desktop view to support the work of supervisors and other knowledge workers. Among other things, data utilized from the vehicle management system and indicators related to working time now complement the reporting package.  

Growth for productivity with successful data warehousing 

A successfully implemented data warehouse contains well-documented, high-quality, quantified and time-related information that is easy to find and access. By providing a single data layer for the data used from different sources as well as the processed and combined data, the data warehouse serves the information needs of different user groups better and more efficiently. 

Data warehousing increases work productivity and an organization’s ability to respond to change through lightweight or deep-drilled analytics. Therefore, it is worth to be planned and built properly so that the information is available and accessible at the right time. This way, the risks of correcting costly errors and omissions are also reduced. 

A good data warehouse is built piece by piece into a unified entity, into which data is systematically modelled around each case. Well-implemented information models support the interaction between business and technology as well as guide information management and its development. 

The future of knowledge management 

Data warehouse automation will continue to increase significantly due to its cost efficiency. More data is constantly stored in data warehouses, a significant part of that data is non-structured and comes from sources outside the organization. In this case, the role of data visualization and analysis is further emphasized as data changes and grows with the needs and goals of organizations. 

Does your organization have a foundation for knowledge management, or would you need to use your organization’s knowledge more deeply? Contact us and we will find the right solution for your situation together without wasting time and budget.  

Jere Palanne
CTO, Partner

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