Topic
Cloud data platforms
Warehouses and lakehouses where licensed data is loaded and joined.
- A market dashboard on company signals in Data Studio (Looker Studio)How to shape the market series table for charting, build rate, index and growth charts with an industry filter, and avoid the aggregation and base-date traps that distort a weekly series.
- Apache Iceberg tables for licensed external dataA table format decides how licensed files are stored, partitioned, loaded again and read back. This guide works through those choices for Fokals bulk exports.
- AWS Data Exchange: a guide for buyers of company dataA buyer's guide to AWS Data Exchange: the five data set types, how subscriptions and entitlements work, how revisions reach your bucket, and how to load company data that is delivered direct.
- AWS Glue pipelines for licensed external dataLand the files, catalogue them without letting a crawler rewrite your schema, process only new days with job bookmarks, and check every load. Worked on the Fokals tables.
- BigQuery sharing (Analytics Hub): a guide for buyers of company dataWhat subscribing to a listing creates, what a linked dataset does and does not allow, how a commercial purchase works, and what to ask a provider before you rely on it.
- Company signals as context for Amazon Bedrock applicationsCompany signals are dated rows with sources. This guide compares an Amazon Bedrock knowledge base with a tool call over your own tables, and shows how to keep every answer dated and cited.
- Company signals as grounding data for Vertex AIWhich of Google's grounding options fits company signals, how to expose BigQuery tables to a Gemini model with typed queries, and how to return dates and sources so an answer can be checked.
- Data sharing in Oracle Autonomous Database, explainedVersioned and live shares, Delta Sharing as provider and as recipient, and the controls a licensing team needs to map: who receives the data, for how long, and what is logged.
- Databricks Marketplace: a guide for buyers of company dataFrom listing to read-only catalog: what a Databricks Marketplace listing contains, how instant and request access differ, how non-Databricks buyers connect, and what to ask a provider.
- Delta Sharing, explained for data licensing teamsThe open protocol behind Databricks Marketplace: how providers, shares and recipients work, what changed in its name in 2026, and what a licensing team should settle when data is shared.
- Feature engineering on company signals in DatabricksWhich timestamp to key a feature table on, how to join labels as of a date, and the leakage traps left in daily and weekly company data, with worked SQL and Python.
- Governing licensed data with Unity CatalogA worked Unity Catalog design for licensed data: a catalog per agreement, group grants, licence tags, lineage and share checks, with the limits of each control stated.
- Grounding Azure AI applications on company signalsTwo routes to answers that carry a date and a source: a search index for announcements and a SQL tool for counts and trends, with the tables, the tool definition and the citation rules.
- Joining licensed company data to CRM tables in SnowflakeA worked join model in Snowflake SQL: a domain normaliser, a bridge to the company ID, subdomain matching, a match-rate report and a view for sales teams, with the pitfalls named.
- Loading company data into Amazon RedshiftWorked SQL for loading company data into Amazon Redshift: a table definition, COPY from S3, the SUPER type for JSON cells, and a daily incremental load that can run twice without duplicates.
- Loading company data into BigQueryA worked path from files in a bucket to partitioned BigQuery tables: LOAD DATA with an explicit schema, JSON columns for the object cells, MERGE for daily files, and checks after each load.
- Loading company data into Databricks with Auto LoaderA worked load of Fokals files into Databricks: landing in a volume, bronze with Auto Loader, typed silver tables kept free of duplicates with MERGE, and a gold join to your identifiers.
- Loading company data into Oracle Autonomous DatabaseA worked load of company CSV and JSON files into Oracle Autonomous Database with DBMS_CLOUD, with the format options that decide the result, the log tables, a load pipeline and JSON queries.
- Loading company data into Snowflake from files and an APIA worked pipeline from delivered files and API pages to history tables: stages, loading CSV by header name, JSON Lines into VARIANT, and an idempotent daily MERGE.
- Microsoft Fabric: bringing external company data into OneLakeWhere external company data goes in Fabric and how it gets there: lakehouse or warehouse, files kept as they arrive, loaded into Delta tables on a daily schedule.
- OneLake shortcuts and external data sharing in Microsoft FabricShortcuts point to data without copying it, and external sharing opens it to another tenant. Here is what each does and what to settle in a data licence before you use them.
- Power BI reports on company signalsA model for hiring and technology trends in Power BI: which tables are facts, which measures must not be summed, how refresh fits write-once tables and how row-level security keeps viewers in scope.
- Querying company data on Amazon S3 with AthenaHow to query bulk company files with Athena: JSON Lines external tables over your own S3 prefixes, daily partitions with partition projection, and converting to Parquet with CTAS.
- Salesforce Data Cloud and external company dataData Cloud is now named Data 360. This guide covers the documented ways to bring in company data, the choice between copying and querying in place, and account matching.
- SAP Datasphere: adding external company data to business dataWhere licensed company data lives in SAP Datasphere and how it meets business partner records: a dedicated space, loaded tables, a mapping table and views that expose only what the licence allows.
- Snowflake Marketplace: a guide for buyers of company dataFrom listing page to first query: how a Snowflake listing reaches your account, how trials and billing work, which questions to put to a provider and how to load data delivered direct.
- Snowflake Secure Data Sharing, explained for licensing teamsWhat is copied, who pays, how access ends and what a licence must still say, whether data reaches you as a Snowflake share, a listing, a reader account or as files you load.
- The SAP Datasphere Data Marketplace for data buyersWhat a buyer reads on a product page in the SAP Datasphere Data Marketplace, how licence keys and delivery types work, and the routes for loading data delivered direct.
- Using company signals with Snowflake Cortex AI functionsWhich Cortex functions exist today, worked SQL to summarise a watchlist's announcements and to search them, and the governance, cost and licence questions to settle first.
- AWS Data Exchange vs Databricks MarketplaceAWS Data Exchange sells subscriptions billed by AWS and delivers in five forms. Databricks Marketplace lists data shared through OpenSharing and sends commercial transactions through the provider.
- BigQuery sharing (formerly Analytics Hub) vs Snowflake MarketplaceTwo ways to receive data without loading a file, set side by side as Google and Snowflake document them: access, payment, regions, what you may copy, and how data delivered direct sits beside a listing.
- Databricks vs Microsoft Fabric for external company dataTwo lakehouse platforms set side by side for a vendor's daily files: Delta Lake with Unity Catalog beside OneLake, OpenSharing beside external data sharing, and the tools each gives you to fence licensed data.
- Delta Sharing vs Snowflake Secure Data SharingOne is a protocol that any client can speak, the other a feature inside one platform. A comparison built on two questions a licence turns on: who can be a recipient, and what ends access.
- Microsoft Fabric vs Snowflake for external company dataOne daily vendor file taken into a Fabric warehouse and into Snowflake: the two COPY INTO dialects, a JSON cell on each, what each bills for, and how the platforms read each other's tables.
- Snowflake Marketplace vs AWS Data ExchangeA share in your Snowflake account, or files, an API and in-place access on AWS: the delivery mechanics, product types and billing of the two marketplaces, set side by side for buyers and providers.
- Snowflake vs BigQuery for external company dataOne vendor file loaded into both warehouses: COPY INTO beside LOAD DATA, VARIANT beside JSON, shares beside linked datasets, and what each documented pricing model means for a daily feed.
- Snowflake vs Databricks for licensed company dataOne daily vendor file taken through both platforms: stages and COPY INTO beside volumes and Auto Loader, VARIANT on each, then sharing, governance and AI functions as each vendor documents them.
- Data lakehouseA data lakehouse puts a table layer over open files in object storage. This entry explains the parts, how vendor files are landed, and why time travel is not point-in-time data.
- Data sharingData sharing gives another organisation read access to tables you hold without sending a copy. This entry explains how it works and what it means for licence terms.
- Data warehouseA data warehouse stores integrated, historical data modelled for analysis. This entry explains grain and keys and shows how vendor files fit a warehouse model.