# Best analytics tools for software development firms

<p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">I’m helping a couple of software teams evaluate the <a class="a a--md" elv="true" href="https://www.g2.com/categories/data-science-and-machine-learning-platforms"><strong>best analytics tools for software development firms</strong></a> because their product and engineering data is growing fast, and they want a setup that supports analytics <em>and</em> ML without a huge platform rebuild.</p><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true">Here are a few I’m considering:  </p><ul>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/databricks/reviews"><strong>Databricks</strong></a>: Unified platform for data engineering, analytics, and ML workloads on big datasets. Often used when teams want notebooks + pipelines + ML workflows in one place.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/snowflake/reviews"><strong>Snowflake</strong></a>: Cloud data platform used for scalable analytics and centralized data access. Common when teams want fast querying and shared data foundations for downstream ML.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/google-vertex-ai/reviews"><strong>Google Vertex AI</strong></a>:  Managed ML platform for training, deploying, and operating models in Google Cloud. Useful when product teams want a managed path from experimentation to production.</li>
<li>
<a class="a a--md" elv="true" href="https://www.g2.com/products/amazon-sagemaker/reviews"><strong>Amazon SageMaker</strong></a>: Managed ML service for building, training, and deploying models on AWS. Works well when your stack is already AWS-heavy, and you want ML ops tooling included.</li>
</ul><p class="elv-tracking-normal elv-text-default elv-font-figtree elv-text-base elv-leading-base elv-font-normal" elv="true"><strong>If you’re in a software dev org, what’s actually been the best platform for analytics, and what did you wish you’d standardized earlier?  </strong></p>

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