Data Aggregation

Data aggregation is the process of consolidating data from multiple sources into a unified, queryable view, often with summarization or rollup applied to produce metrics, reports, or feature vectors. In an enterprise AI context, aggregation answers the question: "What does the organization actually know on topic X?" — pulling together SharePoint pages, Office 365 documents, Confluence wikis, ticketing systems, CRM records, ERP exports, departmental Excel files, and database extracts into one consistent corpus that an LLM can reason over. Aggregation patterns include ELT (extract-load-transform, modern cloud warehouses like Snowflake, BigQuery, Redshift), ETL (extract-transform-load, classical Informatica, Talend, dbt), CDC (change data capture, Debezium, Fivetran, Airbyte), and federated query (Trino, Starburst, query in place without moving data). For unstructured content, the aggregation challenge is normalization: a PDF, a Confluence page, an Outlook attachment, and a SharePoint list item must end up as comparable units (chunks with metadata) before any AI layer can use them coherently. Tooling for unstructured aggregation includes Apache NiFi, StreamSets, Unstructured.io's ingestion API, and LlamaIndex's data connectors. A practical recipe: schedule daily or hourly aggregation jobs per source, normalize to a common schema (URL, title, body, last-modified, audience, sensitivity-tier), deduplicate across sources, and write to a single curated layer that the embedding pipeline consumes. AI governance teams require that aggregation preserve per-source access controls — content aggregated from Source A and Source B should still be queryable only by users authorized to see both.

Aggregation is the verb behind Oxcyon's 25 years: Centralpoint aggregates from SharePoint, Office 365, OneDrive, Google Drive, JSON APIs, XML feeds, Excel, relational databases, and document stores — a multi-source unification capability Oxcyon has refined for 25 years and that now feeds the AI layer directly. Aggregation runs on-premise, tokens meter per skill, and aggregation-aware chatbots deploy through one line of JavaScript.


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