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Tag: Datameer

Replace Alteryx Self Service Chaos

Posted on 2025-04-09 - 11:20 pm by
Alteryx Migration

At DataTools Pro, we are longtime users of Alteryx and have termed it the ultimate data Swiss-Army knife. Having to replace Alteryx for enterprises is not an easy decision because skilled Alteryx builders are wildly productive turning data into information.

The power of Alteryx is the ability to rapidly transform and validate disparate data without writing code. This pattern remains ideal for analysts who struggle to automate complex data workflows in Excel. Data engineers who would typically write code to transform data sometimes lack business context and experience understanding acceptable validation rules. The symbiotic rise of Tableau allowed Alteryx as a high quality “ETL for Analysts” solution thrived.

Alteryx Rocketship : The State of Data in 2010-2020

  1. Data management and business intelligence were centralized but moving toward self service
  2. Analytics turn times were measured in quarters and years
  3. Data and BI teams were severely backlogged and unable to meet demand
  4. Data was spread across windows file shares and on premise databases
  5. Large enterprise data warehouses were extremely slow to develop
  6. The rise of self service visualization with Tableau created the perfect symbiotic relationship

No-Code can get in the way of efficiency

A few years ago, while using Alteryx with Snowflake, I found myself leaning on the Alteryx Python tool to handle extreme edge cases where 10-15 nodes could be expressed in a few lines of code. For example, a rolling 60 business day (minus bank holiday) window function is something we created as a UDF in Snowflake.

Shift from ETL to ELT

As a head of data and analytics and now as a consultant using Snowflake has been a game changer. As an enabling technology, it has democratized the data warehouse the same way Alteryx did for no code ETL 15+ years ago. Now, I can pump millions or hundreds of millions of rows into Snowflake with low storage costs, process, and then deliver to any analytics tool securely.

There are many new drag and drop, flow based solution that have learned and improved on the ETL tools that came before. When it comes to analytics-focused data flows for Snowflake, Datameer has long been my choice after discovering them looking for a low code solution to handle the transformation layer.

Demystifying Alteryx Flows like Messy Code

A SQL engineer can solve problems with un-optimized, difficult to follow code. Similarly an Alteryx builder can create overly complex flows, or worse stitch many flows together that can take days to decouple. In 2025, I can take tens of thousands of lines of SQL code, pump it into ChatGPT and immediately demystify, document and understand what to do next. An Alteryx installation that has grown over time naturally accumulates technical debt.

To demystify Alteryx, there are numerous tools that we use to inventory and understand Alteryx Flows.

Why Replace Alteryx with Snowflake Powered Data, Analytics and AI

Cost, complexity and operational risk are the three consistent themes we see for clients looking for alternatives to Alteryx. There are numerous tools in the market for no-code flows that have advanced beyond Alteryx. We are happy to introduce you to them.

If your enterprise’s data strategy calls for using Snowflake as the core data platform for analytics and AI, we highly recommend Datameer!

We are here to help you inventory and plan your migration

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DataTools Spotlight: Datameer is our Snowflake Tool of Choice

For this month’s DataTools spotlight, I wanted to share my long time favorite for Snowflake tool, Datameer. Years ago, I found Datameer solved my slow Snowflake adoption problem. My team was loaded with requirements but had only one data engineer on staff. Historically we used Alteryx and Tableau prep to get by. Extracting data from…

Continue Reading DataTools Spotlight: Datameer is our Snowflake Tool of Choice

DataTools Spotlight: Datameer is our Snowflake Tool of Choice

Posted on 2025-03-09 - 9:29 pm by
Datameer

For this month’s DataTools spotlight, I wanted to share my long time favorite for Snowflake tool, Datameer. Years ago, I found Datameer solved my slow Snowflake adoption problem. My team was loaded with requirements but had only one data engineer on staff. Historically we used Alteryx and Tableau prep to get by. Extracting data from Snowflake to transform and insert into Snowflake was a pattern that didn’t make sense. Years ago, I shared the story how slow adoption turned around with Datameer where we delivered 20 models to production in a couple of months. That resulted in us turning off Tableau Prep and Alteryx.

As that story progressed, times got tough and we had to do more with fewer human resources. Datameer was the only way we could keep up with change management and new requests. Those are the stories you don’t lead with as case study, but I can openly share that experience now with my own clients as DataTools Pro.

Snowflake tool - Union

In 2024, I continued writing about my Snowflake experiences with Datameer. In the last year, Datameer has continued to level up its enterprise grade features while continuing to add time savings features for individual contributors.

When I use Datameer for Snowflake

There are three primary scenarios where Datameer makes sense for Snowflake customers.

  1. Accelerating Snowflake adoption and deployment of data models
  2. Empower analysts on Snowflake while keeping data in Snowflake
  3. Eliminate self-service data prep tech debt

To elaborate on this third point, I have recently run into massive, complex Tableau + Alteryx self service installations. I love Alteryx and Tableau for data exploration and dashboards as an individual contributor. However, watching enterprises lose control over the volume, velocity, and cost of self-service is painful to see.

In recent years, the pendulum has swung back, as companies have invested in modern data platforms like Databricks, Snowflake, Fabric, and Google Cloud Platform. When it comes to Snowflake, as a practitioner, I haven’t found anything that makes it easier than Datameer to wrangle and prepare data in Snowflake for business consumption. I have started chronicling how to convert Alteryx to SQL Snowflake.

Datameer flow

Enterprise Snowflake tool features that matter

From scheduled data delivery via email to publishing fact tables for business intelligence tools like Tableau and Power BI, Datameer provides speed, control, governance, lifecycle management, and cost management in one package.

  • Native Snowflake means data remains in Snowflake
  • A user experience built for speed
  • No-code where you want it, low-code where you need it!
  • Seamless SDLC, code rollback and environment promotion management
  • Generate views or materialize tables
  • Built in data validation and exploration
  • Removes proprietary tool lock-in and points of failure.
  • Predictable enterprise pricing

I was happy to be an early adopter of Datameer while working for a small enterprise. Now, I get to use Datameer once again with medium and large enterprises. If you are on Snowflake or making the move to Snowflake and need to accelerate adoption, feel free to reach out, and I’d be happy to give you a walkthrough.

Datameer Resources

Tutorial: Join and Analyze Two Tables

Tutorial: Column Profiling and Analysis

Tutorial: Data Exploration and Sharing

Convert Alteryx to SQL

Article: Alteryx to Snowflake Guide

Previous Spotlight

Webinar: Streamlining Data Migration to Salesforce in 2024 using Datameer and Snowflake

Posted on 2023-04-09 - 10:00 am by
Datameer Webinar

View our recorded webinar with Datameer and Data Tools Pro discover how you can optimize your Salesforce data migration process in 2023 using a reverse ETL process powered by Datameer and Snowflake. This webinar will be presented by Datameer and Ryan Goodman, creator of Data Tools Pro. Ryan will showcase how Datameer has been the secret sauce to accelerate a reverse ETL data stack to effectively prepare, transform, and analyze data.

Whether you’re a Salesforce administrator, a data analyst, or data professional, this webinar will equip you with practical insights to streamline your data migration. Don’t miss out on this opportunity to learn and ask live questions how to enhance your data migration practices.

What you will Learn?

During the webinar, we’ll cover , real-world examples of successful reverse ETL scenarios for Snowflake specifically for Salesforce. Additionally, Ryan will share best practices and pitfalls to avoid during a typical Salesforce.com data migration.

On Demand Recording

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How my Snowflake Powered Lead Distro Test Turned Out to be Reverse ETL

Posted on 2023-04-03 - 11:41 pm by
Snowflake Cloud Data Pipelines for Reverse ETL

A year ago, I worked on a small project to help us improve our data driven funnel. I learned what I called “Snowflake to Salesforce analytics sync” had a more buzzworthy term called “Reverse ETL.” This article shares some of the lessons learned along the way and some thoughts about where reverse ETL is headed.

Low Level of Effort Solution

All of the data and metrics were already available and calculated in Snowflake for reporting, so the process to push those measurements back into a Salesforce object using Azure Data Factory was quite simple.

The transformation work was prepared using Datameer on top of Snowflake which I had previously written about: Slice Through your Snowflake Data like a Buzzsaw with Datameer

Read more on Medium Blog

Datameer is a Cutting Edge Solution for Snowflake Data Preparation

Posted on 2023-01-23 - 1:34 am by
Slice through your Snowflake data with Datameer

Snowflake has helped democratize the data platform eliminating layers of technology and administrative traditionally required to enable data workers. The next generation of data preparation tools arrived in recent years and continues to accelerate the process for preparing business ready data assets.

In my previous role managing data and analytics, I had a big problem. All of my data was staged in Snowflake but data engineering was backlogged with requests and my analysts were stuck between SQL and the last generation of desktop BI data preparation tools. I solved this problem and tripled my team’s throughput with Datameer.

Datameer is a native Snowflake data preparation and analysis solution that does not require extracting any data out of Snowflake. I used for all of my BI reporting and dashboard projects, allowing me to roll out 3 times more business ready data assets in 2 months than the first 5 months of my Snowflake initiative.

There are a few key features of Datameer that helped us wrangle data faster. Enterprise data is imperfect, so you need the right tools to profile, explore, and understand imperfections while you build.

Data-Driven Join Analysis

One of these features is Join Analysis, which offers unmatched Rows that enable me to quickly see which records fall out of the left and right side of the join. With this feature, I can easily identify records that are missing IDs or recognize that I didn’t fully understand the grain of data before I joined. The Join Keys analysis feature also identifies duplicate records and highlights which data source is causing duplicates or potential cartesian products as a result of duplicate keys. These features enable me to understand my data both inside and out of each join, allowing me to move forward more efficiently in my data flow.

Tutorial: Learn how to join data intelligently with Datameer

Explore and Share Data in One Place

Another useful feature of Datameer is inline no-code Data Exploration. This feature is essential when exploring data and validating it with collaborators. Datameer provides intuitive and fast exploration capabilities so you can create many cuts of data through your data pipeline. You can employ filtering, aggregation, binning, and sorting. It only takes about 5 minutes to master this feature, and it has enough functionality to cover most real-world slicing and dicing. For repeatable or reusable scenarios, the exploration nodes feature enables me to make my exploration view available or deploy it as its own view back to Snowflake for recurring validation.

Tutorial: Explore and share data in Datameer

One Click Field Profiling

Field Exploration is yet another useful feature of Datameer, as it prepares a summary profile for each field and provides a visual reference point for quickly identifying outliers, NULLs, district values, and unique records. This feature is similar to Snowflake and helps me quickly and efficiently understand my data.

Tutorial: Field Profiling and Exploration

Datameer is No-code where you want it.. SQL Coding where you need it

Datameer offers a no-code user experience that will technically allow you to build and deploy business intelligence views and tables without writing a line of code. There are conversely many experienced SQL developers who are more proficient writing SQL than using no-code interfaces. Datameer is best of both worlds because you can visually abstract your SQL code into a flow and have all Snowflake SQL functions on hand. This way you can still beneifit from the aforementioend features while coding. Datameer with generate your SQL as a CTE that runs natively on Snowflake.

Change Tracking and Revisions

In addition to a rich meta and tagging, Datameer offers deployment history and version control natively, allowing you to comment revisions, single click restoration to previous deployments in Snowflake, and full access to the SQL code.

Overall, I am impressed with Datameer’s capabilities and look forward to every release with incremental updates focused on bringing data teams and data analysts together in a practical solution.

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