How cloud computing, the Python stack, data warehouses, and the growth of SaaS platforms are poised to change the face of data integration.
Cloud computing, big data, machine learning, data lakes, data warehouses — no doubt, if you’ve been following the tech world you’ve heard these buzz words. These trends and the resulting technologies have changed the world and are continuing to unearth new opportunities for innovation.
If you looked at the face of data integration 15 years ago when Talend, now a behemoth in the space, launched Talend Open Studio the words that came to mind were “drag and drop” interface, SQL-based, on premise, and Windows native. Since then, things have changed dramatically.
“We have observed an industry transition to cloud-based technologies…
The tools that make creating data integration pipelines easier than ever for B2B developers
If you’re a B2B developer building a new product one of the earliest and most fundamental decisions in the product development phase is
How the heck will I get customer data into the product?
Whether you’re building:
- accounting software that needs to pull invoices from NetSuite, Intuit Quickbooks, or Sage Intacct
- sales software that needs to pull CRM data from Salesforce and HubSpot and billing data from Stripe or Chargebee
- marketing software that needs to pull analytics data from Google Analytics or file uploads
- or any other type of SaaS software
The trend is the same: data is only getting…
Building a lightweight Quickbooks data integration pipeline using Python
If you’re a B2B developer building a product, one of the earliest product development phases is creating a data integration pipeline to import customer data.
In this article, I’ll show you how to leverage Singer’s tap-quickbooks to extract data from Quickbooks. From there I’ll walk you through how to parse the JSON output data from Singer using target-csv and standardize it using a simple Python script.
Notes
The code for these examples is available publicly on GitHub here, along with descriptions that mirror the information I’ll walk you through.
These samples rely on a few open source Python packages:
Building a lightweight Salesforce data integration pipeline using Python
If you’re a B2B developer building a product, one of the earliest product development phases is creating a data integration pipeline to import customer data.
In this article, I’ll show you how to leverage Singer’s tap-salesforce to extract data from Salesforce. From there I’ll walk you through how to parse the JSON output data from Singer using target-csv and standardize it using a simple Python script.
Notes
The code for these examples is available publicly on GitHub here, along with descriptions that mirror the information I’ll walk you through.
These samples rely on a few open source Python packages:
The growing debate over the viability of building on open source Singer taps
Singer is an open-source standard for writing scripts that move data built by the folks over at Stitch. The open source project was introduced by Stitch to make the process of creating data integration “connectors” more standardized and easy — an attractive pull for developers.
In fact, both closed source projects like hotglue and open source projects like Meltano are building off Singer taps to offer platforms that make the process of creating data integration pipelines easier for developers.
However, there is a growing debate over the feasibility of building data pipelines on top of Singer taps. Why?
Airbyte, a…
An embeddable data integration tool for B2B developers built on the Python ecosystem — now in open beta!
Hello from the hotglue team! This is part of an ongoing series of posts where we keep track of our updates and milestones. You can also follow us more closely on IndieHackers!
What is hotglue?
A quick refresher for those who aren’t familiar with hotglue: we make a data integration tool to get customer data into B2B apps.
Our software embeds into apps, enabling developers to support more data sources, manage data cleansing & transformation, and offer a self-serve experience to their users. With hotglue, any developer can build a data integration pipeline in minutes without months of development and maintenance.
Updated demo
We’d love…
An embeddable data integration tool for B2B developers built on the Python ecosystem — now in closed beta!
Hello from the hotglue team! This will be the first in an ongoing series of posts where we keep track of our updates and milestones. You can also follow us more closely on IndieHackers!
What is hotglue?
A quick refresher for those who aren’t familiar with hotglue: we make a data integration tool to get customer data into B2B apps.
Our software embeds into apps, enabling developers to support more data sources, manage data cleansing & transformation, and offer a self-serve experience to their users. With hotglue, any developer can build a data integration pipeline in minutes without months of development and maintenance.
Updated demo
…
Clean and transform raw data into an ingestible format using Python
In this article, you’ll learn how to work with Excel/CSV files in a Python environment to clean and transform raw data into a more ingestible format. This is typically useful for data integration.
This example will touch on many common ETL operations such as filter, reduce, explode, and flatten.
Notes
The code for these examples is available publicly on GitHub here, along with descriptions that mirror the information I’ll walk you through.
These samples rely on two open source Python packages:
A light-weight platform to solve data integration for startups.
hotglue is a cloud-based embedded ETL platform designed to help B2B SaaS firms minimize the data integration phase of onboarding new users to your app.
Today, we’re excited to show off an early demo and get some feedback from the community. Feel free to leave comments and ask questions!
Demo
Before we get into the meat of it, we think the best way to explain something is to show it. Without further ado, check out our demo below!
We’d love your feedback and are happy to clarify if you have any questions. …
Solve data onboarding and enable customers to adopt faster.
- For most SaaS B2B firms, the biggest barrier to adoption is getting customer data into their product.
- Traditional ETL (extract, transform, load) solutions target large enterprise firms. Startups cannot afford to use these, and are reduced to building their own solutions or painstakingly transforming data by hand.
- Embedded ETL is a newer approach designed to give startups a real ETL tool. Instead of shirking the responsibility of on-boarding customers, providing ETL from within the product translates to vastly reducing the barriers to adoption for your product.
Data is Your Traction Problem
Most B2B software vendors fail to realize that one of their biggest adoption problems…
Hassan Syyid
Co-founder at hotglue, CS at UMD
