Alteryx + Databricks for Manufacturing: Turn Raw Data into Gold

What's New   |   Alex Gnibus   |   Apr 5, 2023

One definition of alchemy is the speculative science of turning base metals into gold. Alchemy saw a lot of hype back in medieval times, but we haven’t yet figured out the secret.
Industry 4.0 is a lot like alchemy; we’ve heard a lot about its potential, and whoever figures it out has the chance to win big ($3.7 trillion big).
But while Industry 4.0 has been a top priority for the manufacturing sector, McKinsey estimates that only 29% of companies are capturing value from Industry 4.0 solutions. Like alchemy, Industry 4.0 seems to be failing to deliver on the hype.

Finding Value in Manufacturing Data

Unlike alchemy, though, getting value from data isn’t a mysterious process. We have known methods for turning data into gold (or at least better insights and more money).
So where are manufacturers getting stuck?
Legacy analytics stacks can’t handle the growing amounts of data coming from IoT devices and complex production systems
Slow data processes and silos prevent real-time insights Manufacturers focus too much on technology tools and not enough on the business departments using them – leaving the data transformation to a few employees instead of the entire organization.

Alteryx + Databricks = Gold

Alteryx and Databricks make it easier for manufacturers to get unstuck and start going for gold.
Databricks recently unveiled the Lakehouse for Manufacturing. Lakehouse for Manufacturing is the only enterprise data platform that unlocks the value of all your data at the lowest TCO. It empowers manufacturers to get real-time insights, improve responsiveness and accelerate innovation with data and AI.
As a partner in the launch, Alteryx is a great fit for manufacturers who want to establish an analytics stack with Databricks and deliver the value that Industry 4.0 promises. How do Alteryx and Databricks help? By enabling employees of all roles and skills to collaborate. Alchemy isn’t a one-person job, after all. You need your business experts (who know the data sources and use cases) and your technology experts (who know the analytic techniques and coding languages) to work together on the data transformation process.

The Medallion Framework

The medallion lakehouse architecture is a good way to put this collaborative approach into action. The medallion lakehouse framework takes a page from the alchemy playbook: you go from bronze (raw), to silver (validated), and then gold (enriched). This architecture guarantees atomicity, consistency, isolation, and durability as data goes through transformations before being stored in Delta Lake on Databricks for efficient analytics. The idea is to improve the quality of data as it goes through each phase, from the raw data you collect to business-level, consumption-ready tables.

The Medallion Framework

Bronze Layer: Collect and Centralize the Raw Data

The bronze layer is where you’re getting your raw data centralized and organized. Manufacturing companies deal with an overwhelming number of data sources and data types. Transaction data, inventory management data, IIoT (industrial IoT) data from the production line, and more. The Databricks Lakehouse architecture provides a place to centralize data of all kinds (structured and unstructured), making it available for business analysts to then transform and analyze in Alteryx.

Silver Layer: Clean, Prep and Transform Data

Here’s where you join, cleanse and prep the data to get it ready for advanced analytics. Using Alteryx’s intuitive, no-code and code-friendly interface, employees across departments can jump in and do this step themselves. That way, the people transforming and validating the data are the same people who understand what the data will ultimately be used for.

Gold Layer: Curate Business-Ready Datasets for Manufacturing Use Cases

The Gold layer has consumption-ready data sets. This means the data is organized into clean, complete and read-optimized data sets that are easy to find and analyze – such as “Shipping History by Warehouse Location” or “Warranty Claim Records.” The Gold layer also makes it easier to compare datasets from different departments for richer insights – like connecting IoT data to financial and customer databases to monitor the business impact of adopting smart devices. This breaks the silos that prevent manufacturers from fully benefitting from Industry 4.0 initiatives. Here are just a couple other ways manufacturing customers can implement the Medallion framework and use Alteryx and Databricks together to solve Industry 4.0 challenges:

  • Assortment and Inventory Planning: Assortment planners can import sales and inventory data from Databricks Lakehouse Platform, combine and prep the data in Alteryx Designer to curate a Gold-level dataset, then run the dataset in Auto Insights to share findings quickly with the director of retail operations.
  • Logistics and Shipping Analytics: Your supply chain analyst can use Alteryx to identify which orders can be fulfilled at which distribution centers, by examining available inventory and choosing the distribution center closest to the point of delivery.

In the beginning of this post, we defined alchemy as the science of turning metals into gold. But here’s another definition for alchemy: The process of transformation. By that definition, analysts are also alchemists! Given the right tools, they can make seemingly magical transformations happen, and Databricks and Alteryx are those tools.