Data warehouse – in short
Data warehouse – in short
Modern companies succeed using knowledge-based management. Data warehouses, which integrate and consolidate the data available throughout the organization are the foundament for business analytics / intelligence solutions. Data warehouses are the starting point for the so-called IT analytics (data science) and creating deep analysis based on them.
summ-it provides comprehensive service – from business analysis through implementation to maintenance of implemented solutions.
Data warehouse – for whom?
Medium company
Big company
Corporation
INDUSTRIES AND SECTORS: retail and e-commerce, finance and fintech, insurance, industrial production, public sector, health care.
The data warehouse is an ideal solution for an organization with extensive data resources distracted between different systems, departments or even geographical location.
Data warehouse – benefits
Data warehouse – solution architecture and functionality
Distributed sources supply data warehouses using the ETL solution: Extract, Transform and Load. His task is to make them coherent. Due to the amount of information, based on the central warehouse, thematic warehouses are built (data marts) containing data that describe narrow areas of the company’s operation.
Data warehouses allow:
Data warehouse – description and structure of the solution
Heterogeneity and distributed IT systems are common challenges facing organizations. In such cases, access to data is inefficient, and the picture of the situation built of fragmentary materials – incomplete or incorrect.
The data warehouse not only aggregates, but also integrates data from different systems according to one structure and model. Based on this, systems are created to provide management with knowledge in the form of intuitive tools for preparing analyzes and reports. However, they provide the basis for making accurate decisions.
Data Warehouse:
Data warehouse – solutions and services:
Data warehouse – 3 steps to implement
Determining the purpose of building a data warehouse
Analysis of the organization structure and available data sources
Creating a business case – implementation treated as an investment and KPI definition