DataAI ETL Tableau - Customer-Ready Evaluation

Product: Tableau

Distribution: Customer-ready evaluation

Source: DataAI_ETL_Tableau_Evaluation/docs/INSTALLATION_AND_USAGE.md inside DataAI_ETL_Tableau_Evaluation.zip

Package SHA-256: 03606b38ac48590aea55ce633548e1de3bd57b457729b25ca2b1341f6b06c517

Download customer-ready package | Download checksum | Read the evaluation license

Start here: Download one customer-ready ZIP. It already contains the DataAI libraries, product assets, documentation, samples, licenses, internal checksums, and local verification files for this integration. Spark, Hadoop, vendor products, and proprietary drivers remain customer-provided.

Tableau: Customer Evaluation Installation and Usage

This is the customer-ready DataAI ETL evaluation package from Yanbor LLC, provider of the DataAI product. DataAI runs inside the customer's pipeline; it is not a hosted service and makes no required DataAI network call.

Prerequisites

Tableau Desktop for the included Accelerator
Java 17 and Apache Spark 3.5.0 with Scala 2.12 for live DataAI processing
Customer-supported Spark SQL or Databricks connector for live data

Installation and first verification

Review LICENSE.md and open install\DataAI_ETL_Accelerator.twbx in Tableau Desktop to inspect the fictional embedded data.
Run smoke-test\run-smoke-test.ps1 to verify the DataAI libraries and Tableau adapter.
Persist the desired Tableau output DataFrames from the customer-controlled Spark application.
Replace the Accelerator sample source with the approved Spark SQL or Databricks tables and validate relationships and refresh.
Complete visual, accessibility, connector, permissions, and supported-Tableau-version checks before purchase.

Evaluation boundary

Use only fictional or approved non-production data.
Review LICENSE.md; the standard evaluation is less than 32 consecutive calendar days.
DataAI software is provided AS IS, with no obligations except those expressly accepted in a signed commercial agreement or order form.
Spark, Hadoop, cloud platforms, BI tools, orchestration products, and vendor drivers remain customer-provided and governed by their respective terms.
A successful local smoke test validates the delivered DataAI artifacts. It does not claim certification on the customer's external platform.

Package layout

install/: platform-specific installer or packages, when applicable.
lib/: DataAI JARs required by Spark-based integrations.
smoke-test/ or nuget-smoke-test/: executable local verification.
docs/: complete function catalog and product-specific guidance.
samples/: fictional evaluation inputs.
platform/: platform-specific examples, notebooks, configuration, POMs, or container-review assets.
PACKAGE_CONTENTS.sha256: SHA-256 for every other file in this ZIP.

Local DataAI Library Smoke Test

This test uses only fictional in-memory rows. It starts local Spark, executes normalization, profiling, required and numeric quality rules, clean/rejected routing, the complete function-catalog check, and iterative matrix balancing. The Tableau package additionally verifies its dashboard and matrix adapters.

Requirements

Java 17.
Apache Spark 3.5.0 with Scala 2.12.
spark-submit available on PATH, or supplied with -SparkSubmit.

Spark and Hadoop are customer-provided runtimes and are intentionally not bundled in the DataAI evaluation ZIP.

Run

From the extracted package root:

.\smoke-test\run-smoke-test.ps1

If the customer's Windows policy blocks direct script invocation and the customer's security policy permits a process-only override, run:

powershell.exe -NoProfile -ExecutionPolicy Bypass -File `
  .\smoke-test\run-smoke-test.ps1

This option applies only to that PowerShell process; it does not change the computer's execution policy.

For an explicit executable path:

.\smoke-test\run-smoke-test.ps1 `
  -SparkSubmit 'C:\spark\bin\spark-submit.cmd'

Success requires exit code 0 and a DATAAI_*_SMOKE_TEST_PASS marker. This local check validates the delivered DataAI libraries. It does not replace the documented validation on Databricks, AWS, Azure, Oracle, Google Cloud, Tableau, Alteryx, or another customer-selected external platform.

Verify the downloaded ZIP

$expected = (Get-Content .\DataAI_ETL_Tableau_Evaluation.zip.sha256).Split()[0]
$actual = (Get-FileHash .\DataAI_ETL_Tableau_Evaluation.zip -Algorithm SHA256).Hash.ToLowerInvariant()
if ($actual -ne $expected) { throw 'DataAI ETL package checksum mismatch.' }