Building ELT Pipelines with No Code Data Connectors

No-code integrations save teams time and accelerate the path to value creation from analytics.

The best data teams don't start from scratch. They are system integrators.

They understand the power of leveraging the best tool for the job, so they can focus their time on creating valuable insights.

Data analytics - The job to be done

I used to run Business Intelligence at LiveRamp (NYSE: RAMP). What was my job? It was to leverage data from across our company to generate unique insights, so our executive team could make better strategic decisions.

Instead of spending my time deploying virtual machines (VMs), managing open source software, or troubleshooting scripts, I was fortunate to spend my time interviewing stakeholders to identify the most valuable problems to solve with data across the company, and then solving the problems with data.

For analytics, you should spend time answering the questions that matter to your business:

• How do you reduce churn?
• How do you attract and retain talent?
• What products are seeing the fastest adoption?
• What products should you deprecate?
• Where is your engineering team spending their time?
• What product packages are most valuable?
• How should you segment your client base?

To spend your time on the things that matter, you should delegate or outsource the rest of the tasks whenever possible. You don't build a visualization tool from scratch. Why would you build a connector from scratch?

Getting started with no-code ELT connectors

What does ELT stand for?

ELT stands for extract, load, transform. ELT connectors sync raw data from systems across the enterprise into a data warehouse or data lake to power analytics and process automation.

It's extremely simple to get started replicating data with ELT connectors. You just configure your data warehouse, authenticate with your data source, and set the data flow live.

ELT Connectors: Build vs. Buy?

Every data team runs into this issue.

You get your major systems connected to your analytics environment, and then you find a bespoke application that isn't supported by the vendor.

Unfortunately, the largest ELT vendors have never ending product backlogs, bigger customers than you, and won't prioritize your urgent request to help automate the data flow you need

At that point, you're stuck. You're left with bad options:

1. Ignore the application, don't sync it to your warehouse, and focus on other business problems, or answering questions with incomplete data
2. Find a hack to get the data into your warehouse. There are countless teams that are exporting data as CSVs, loading them into Google Sheets, and syncing the data into a warehouse from there
3. Script a solution or use an open source framework. Not only does this divert your attention from the job to be done, but now you have a connector as well as infrastructure that you need to maintain and troubleshoot

Find long-tail ELT connectors

As I said above, effective data teams are system integrators. No one wants to have ten data integration vendors, but if you can address 95% of your systems with two, that can save you countless hours and provide you with a nearly complete set of data to answer the questions that matter to your business

Portable focuses on long tail ELT connectors. For example, we connect less popular data sources like Chargebee to Snowflake

We build and maintain long tail ELT connectors

At Portable, we don't differentiate our solution based on the most commonly used connectors - we build and maintain the long tail, custom ETL connectors that matter to your business.