Where the analytics build stands today, what it enables next inside Slack, and the long-term data platform that lets it scale.
Finance data from Deltek and salary data from ADP flow into Salesforce Data 360, where they are governed, and then appear in a Tableau dashboard for leadership.
Salary values are masked as they come in from ADP, before they reach any report or user.
Dashboard viewers see totals such as cost by client, never an individual's salary.
Datana builds with dummy data. A trusted GPJ person uploads the real export in the same format.
GPJ already works in Slack, so the answers can live there too. Slackbot, Slack's built-in AI assistant, can now connect to Salesforce products through official connectors (MCP servers). Once connected, people can ask plain-English questions in Slack and get answers from the same governed data the POC is built on.
Two ways to connect the POC to Slack, both from Salesforce and both respecting each user's existing permissions: Slackbot + Tableau for visual answers from the dashboard's data, and Slackbot + Data 360 for direct questions against the unified data. They can run side by side. The main differences are licensing and the kind of answer you get.
Based on Salesforce and Slack documentation as of September 2026. Final pricing to be confirmed with GPJ's Salesforce account team.
| Slackbot + Tableau | Slackbot + Data 360 | |
|---|---|---|
| Best for | Charts and KPIs from the dashboard's data model, e.g. margin by client | Direct questions and lookups across the unified data, e.g. a specific job or employee group |
| Slack plan | A paid plan with Slackbot. On Business+ each person gets 15 Slackbot messages a week. Enterprise+, or Enterprise Grid / Select with the Slack AI add-on, has no weekly cap. Extra usage can be bought with Salesforce Flex Credits. | |
| Salesforce | A Salesforce org on Enterprise Edition or above, connected to Slack. Each person's Slack account is mapped to their Salesforce login. | |
| Product licence | GPJ's Tableau Cloud works with the hosted Tableau connector on any edition. Each person signs in with their own Tableau licence. Pulse metrics are included. AI insight briefs and Tableau Knowledge need Tableau+. | Data 360 licence, which GPJ already has for the POC. Each person needs the View Data 360 permission. |
| Running cost | Covered by Tableau and Slack licences, plus any Flex Credits used for extra Slackbot messages | Data 360 is usage-based, so queries use Data 360 credits. The POC's production data also needs to be ingested (see section 3 on avoiding this) |
| Security | Runs as the signed-in user. Tableau row-level security applies. | Runs as the signed-in user. Salesforce permissions and Data 360 masking apply. |
As more sources are added, such as Salesforce CRM, a central data warehouse becomes the foundation. Data 360 then reads from it without copying the data, so there are no ingestion charges for those sources. The exception is ADP: salary data goes straight into Data 360 through its native connector.
Both platforms fill the same role, and both connect to Data 360 and Tableau. The choice comes down to how GPJ wants to run it.
| Databricks | Snowflake | |
|---|---|---|
| Both do | Ingestion and transformation, central governance and masking, zero-copy with Data 360 in both directions, native Tableau connection, built-in AI functions | |
| Strength | Flexibility: heavy data transformation, machine learning and custom AI on open file formats | Simplicity: SQL-first and fully managed, with fast dashboard queries |
| Best if | GPJ plans significant AI and ML work and has, or will have, data engineering capacity | GPJ mainly needs a governed store behind Tableau and Data 360, run by a lean team |
| Effort to run | More engineering skill needed | Little tuning needed |
| Cost model | Compute units on top of GPJ's own cloud account. Often cheaper for large pipelines | Compute billed per second. Often cheaper for small, steady workloads |
AI is only as good as the data behind it. Without one clean, unified source, the same question can get different answers. Every new source adds work, so it pays to put the foundation in early.
Data 360 works best on top of a warehouse. As the main store, it charges to ingest every record. With a warehouse underneath, it reads the data where it sits.
Data 360 has a native ADP connector, so salary data flows in on a schedule with no manual exports. It also stays in one place, where the masking rules already built for the POC apply. It never has to be copied into the warehouse, which keeps the number of places holding salary data to a minimum.
This is a later step. The current POC doesn't need it, and everything built now carries forward.