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s than you do learn more login try now book a demo solutions solutions financial intelligence financial data automation data consolidation every erp one source of truth esg sustainability reporting vppa energy procurement analytics industries marketing agencies client reporting analytics retail ecommerce omnichannel data financial services banking fintech hospitality qsr restaurant hospitality analytics product data management keboola platform end to end data platform data streams real time data ingestion data templates pre built data pipelines connectors 300 integrations change data capture cdc for databases transformation sql python r more flow builder visual pipeline builder ai applications applications build custom apps mcp server ai model integration kai your ai data engineering assistant data governance active metadata metadata management opentelemetry otlp endpoint into storage security enterprise security data catalog data discovery activity center monitoring logging resources education resource hub guides whitepapers events webinars live on demand blog news tutorials newsletter stay updated developer resources changelog what s new documentation technical guides developer portal api sdk data academy free courses contact contact us get in touch partners partner ecosystem careers join our team customer stories pricing book a demo try now login frequently asked questions find quick answers about keboola s data platform financial intelligence security and ai capabilities general financial intelligence security ai pricing general what is keboola s pricing model and how does cost work keboola offers a consumption based pricing model combining subscription licensing with usage billing free tier 0 unlimited etl elt pipelines all 700 connectors sql and python transformations 120 minutes in first month 60 minutes monthly thereafter top up available at 0 14 per minute enterprise tier data catalog and sharing data applications dev prod mode with git ci cd vpc deployments soc 2 type ii gdpr hipaa compliance saml and sso dedicated technical account manager data remains intact if credits run out jobs pause but nothing is deleted learn more at keboola com pricing how does keboola differentiate from competitors like fivetran and snowflake keboola s differentiation centers on end to end platform scope versus point solutions vs fivetran while fivetran handles data ingestion only keboola covers ingestion transformation orchestration governance and ai automation in one unified environment vs snowflake while snowflake focuses on data storage and compute keboola integrates with snowflake and bigquery as storage backends while adding the full operational layer ai native architecture sets keboola apart the mcp server enables ai agents to build and manage pipelines via natural language multi cloud flexibility offers deployment across aws azure and gcp without lock in built in governance includes automatic compliance monitoring and policy enforcement natively learn more at keboola com product overview what deployment options and data warehouses does keboola support three deployment models multi tenant saas keboola manages all infrastructure available stacks aws us eu azure eu gcp us eu multi tenant with byodb data stays in customer owned snowflake or bigquery while keboola manages orchestration single tenant complete keboola stack within customer cloud aws azure gcp maximum control for regulated industries supported backends snowflake default backend with full sql support dynamic warehouse sizing native workspaces byodb bigquery full sql support native datatypes direct workspace access byodb additional via connectors redshift synapse oracle exasol teradata firebolt learn more at help keboola com storage byodb who is keboola designed for and what are the ideal use cases keboola serves three primary audiences data engineers build and manage scalable data pipelines without infrastructure overhead data analysts and scientists leverage sql and python transformations plus interactive workspaces for analysis cxos and business leaders eliminate shadow it ai consolidate fragmented data tools and reduce time to insight ai and vibe coders developers building with ai first tools like claude cursor or windsurf can control keboola entirely through natural language common use cases include customer 360 analytics financial consolidation marketing attribution operational reporting and machine learning pipelines across financial services retail marketing agencies and technology companies learn more at help keboola com overview what is keboola and what are its core capabilities keboola is a unified ai data platform designed to support autonomous ai operations with enterprise grade reliability and security unlike point solutions keboola integrates the entire data stack into a single governed environment the platform delivers five core capabilities data integration 700 native connectors for databases cloud services apis and saas applications data transformation sql python r julia and native dbt integration data orchestration visual pipeline building with conditional logic scheduling and event driven triggers ai powered automation build and manage pipelines through natural language via data agent and mcp server data governance built in lineage tracking data catalog metadata management and compliance monitoring learn more at keboola com product overview what are the key components in keboola s platform and connector ecosystem four core components storage table storage snowflake bigquery and file storage s3 azure blob gcs with 7 day snapshots transformations sql python r julia native dbt with input output mapping and version control flows visual orchestration with parallelization conditional logic cron scheduling event triggers components 700 extractors writers applications running as isolated docker containers connector categories databases mysql postgresql mongodb crm salesforce hubspot marketing google ads facebook tiktok erp netsuite sap bi destinations tableau looker gooddata generic connectors extend to any rest api learn more at keboola com product integrations financial intelligence how is keboola financial intelligence priced keboola offers a transparent subscription model designed to scale with your data volume and operational complexity pricing reflects the full financial intelligence solution from integration to governance without locking you into rigid licensing structures keboola financial intelligence is offered as a subscription with tiers that scale by data volume complexity and deployment model hosted vs your cloud the license includes the full financial intelligence solution data integration consolidation logic planning capabilities ai features and ongoing platform updates support most customers see a clear business case based on time saved in consolidation and reporting reduced tooling and infrastructure complexity and the ability to redeploy finance capacity to higher value work for a tailored estimate and roi model based on your entities systems and team size it s best to talk directly with our team how does keboola handle multi entity consolidation eliminations and different fiscal calendars the platform automates group consolidation by standardising journal level data from each entity into a unified model it is built to accommodate variations in erp structures local currencies and fiscal calendars without manual workarounds extracts journal entries from each erp standardises them into a common structure and generates group p l bs cf with proper hierarchies handles multi currency by applying configurable fx rules spot average custom rate tables at transaction level supports entities with different fiscal year ends data is stored at monthly grain and aligned to your group reporting calendar for ytd and prior period comparisons intercompany transactions are tagged at journal level and eliminated or reported according to your group policy with transparent adjustable logic can we use our existing cloud data warehouse and bi tools yes keboola is intentionally built as a bring your own tools platform it leverages your warehouse if you wish to do so as the storage and processing layer and feeds governed data into the bi tool you already rely on keboola runs on top of modern cloud data warehouses like snowflake or bigquery either in a keboola hosted environment or in your own cloud account data is then exposed to any standard bi tool power bi tableau looker thoughtspot excel etc you keep your existing analytics front end keboola simply ensures the data feeding it is unified governed and always up to date how much control do we have over metrics business rules and chart of accounts mapping full control keboola gives finance teams full visibility and authority over how metrics are defined calculated and adjusted nothing is hidden every rule mapping and transformation is accessible and modifiable financial intelligence ships with a standardised financial model and kpis but nothing is a black box you can inspect modify and extend any calculation from intercompany elimination rules to profitability metrics and allocation logic chart of accounts mapping is supported by a coa management app and smart suggestions once mapped new accounts are easy to classify can we compare budget actuals and forecasts and support planning rolling forecasts yes keboola treats budgets actuals and forecast versions as equal citizens in the data model this allows real time side by side comparison and seamless integration of planning updates into the consolidated view financial intelligence supports multiple data versions actuals budget reforecast multiple scenarios through the same pipeline a planning front end with a spreadsheet like interface lets users input or adjust budgets and forecasts with a full audit trail updated forecasts automatically flow back into consolidated views including currency conversion and roll ups so you can run rolling forecasts and scenario analysis without manual rebuilding can we start with a pilot before rolling out to all entities yes and that s often the recommended approach start with 1 2 high impact use cases e g group financial results daily sales connect your core systems and prove value in a single quarter use hard numbers days to close hours mds saved error reduction to build the internal business case then roll out additional entities use cases profitability treasury risk and departments on the same finance data platform how does keboola ensure data quality and accuracy data quality is built into the financial intelligence workflow through validation completeness checks and continuous monitoring keboola ensures that all inputs transformations and outputs remain consistent across systems and entities a dedicated data quality layer validates completeness consistency and reconciliations across entities and systems you can define business rules thresholds and alerts e g intercompany mismatches balance discrepancies missing records and monitor them in real time if you already use data quality tools they can be integrated keboola becomes the central place where clean trusted financial data is assembled for reporting and ai how is ai used in keboola financial intelligence and is it safe for finance data ai is there to augment not replace finance an ai assistant helps build and manage data pipelines and automations directly inside keboola speeding up development for data finance power users an ai chat interface lets business users explore governed data in natural language ask questions request ad hoc cuts generate draft dashboards all against certified datasets all ai usage sits on top of the same governed auditable layer so outputs remain explainable and compliant for finance use cases can we safely give auditors and external parties access keboola supports audit workflows by enabling controlled transparent access to governed datasets external users can be granted scoped permissions while maintaining complete traceability of how every number is produced you can create dedicated auditor roles or workspaces with read only scoped access to the data and reports they need all transformations and adjustments have a clear audit trail what changed who changed it and when this typically shortens audit cycles and shifts conversations from where did this number come from to what does it mean can we build this ourselves on a data platform like microsoft fabric or databricks technically yes but the question is whether building a full finance data foundation is the best use of your team s time platforms like fabric and databricks are powerful toolkits while keboola provides a purpose built ready to use financial consolidation solution building this internally usually requires custom erp api connectors a financial data model with proper hierarchies a chart of accounts mapping ui and governance fx translation rules with full configurability intercompany matching and elimination logic versioning qa reconciliation and completeness checks lineage auditing and sox style controls this typically means 6 12 months of engineering work before finance sees value and ongoing maintenance forever keboola accelerates this dramatically out of the box connectors and financial data model consolidation rules mapping logic and governance baked in end to end automation delivered within weeks and clean integration with fabric databricks if you already use them our philosophy build where it differentiates your business buy where the problem is already solved we already use power bi or tableau why do we need keboola you likely don t need to replace power bi or tableau the real question is what prepares the numbers before they reach the dashboard bi tools visualise data beautifully but they don t solve consolidation governance or financial logic most of the hard work happens before the dashboard extracting and aligning data from multiple erps mapping different coas into a group standard translating currencies accurately identifying and eliminating intercompany transactions performing reconciliation and data quality checks when this logic lives in excel or custom scripts you inherit no audit trail key person dependency manual errors and rework slow change management keboola provides the trust layer beneath your bi automated consolidation and governance certified datasets for reporting drill down to journals and source transactions bi tools continue to do what they do best visualisation the result power bi tableau dashboards your cfo can trust because the data underneath is correct governed and fully auditable what does a typical implementation look like and how long does it take a standard rollout follows five phases and typically delivers first value in 8 weeks preparation environment setup access goal alignment data processing connect 2 3 main source systems initial model quality checks governance business glossary access model report catalogue customisation kpis eliminati...