Data Warehouse Clouds

cloud data warehousing is a means for an organization to store and retrieve curated business decision making information, quickly, accurately, and with high levels of confidence, usually for reporting or visualization it’s pre defined structure allows for cross departmental analysis of business data, that is usually pre aggregated with already applied business logic and rules, with security provisioned profiles to enable a more data governed approach for scaling and enabling self service analytics across the organization lastly, it makes any analysis a team already does in an excel spreadsheet or elsewhere exponentially faster and more consistent a data warehouse is commonly referred to as the “single source of truth” for the organization we recommend that it is always part of an organizations data value chain regardless of an organization’s understanding of a ‘data lake’ an “enterprise data warehouse” (edw) is a common term, and highest level of achievement, for most data warehouse implementations as it implies a holistic representation of the organization’s information snowflake data cloud snowflake docid\ gs6o1ykk2 pyq9sr35dvx bigquery (google) docid\ mvsf9whx39agcxwixrm2s firebolt oracle cloud data warehouse teradata vantage clickhouse our open source data warehouse models open source dw models docid\ nwnkddzzl2dkkynql8 qg why have a cloud data warehouse? in our opinion, and as a fundamental approach to building a datalakehouse, every organization should have a data warehouse as part of the data value chain, regardless of the idea or understanding of a ‘data lake’ a (enterprise) data warehouse enables a single source of the truth for operational and managerial information and data, with curated perspectives on the data that represent the organization, including at a departmental owner perspective well defined key performance indicators (kpis) that drive, and provide the pulse of the business, to track how the organization/business is doing and enables alerting, thresholds, and other measurement abilities corporate and business hierarchy representation of information – this can can be a direct abstract from operational systems (i e erp, crm, pos) to codify and provide taxonomy that represents the organization not the default vendor representation of the transactional data a common example for this is org structure, alternative chart of accounts or p\&l structure, alternative business calendars, etc historical data storage and trend analytics (thus how the organization is performing over time?) master data management (mdm) integration and validation, even potentially a “poor man’s” mdm solution (depending on the organization’s business case requirements) consolidation of multiple data source systems into a single data repository for analytics (for example, multiple gl systems, and/or hr systems) to gain a single source holistic view of the organization (perfect for acquisitions or mergers where decisions need to be made regarding the new formed organization as a whole)