Data Onboarding

What Makes Data Onboarding So Hard?

Written by 
Katrina Kirsch

Data Onboarding is the process of ingesting online and offline data into a product’s operational system(s) in order to successfully use that product. This process is an essential, yet difficult, part of collaborating with customers and partners. 

During onboarding, companies send data to the receiving party's operational systems. But the data comes from various sources and in formats that don't often align with the receiving system. 

Data

Just think of all the different methods and syntaxes people use to share data—spreadsheets, data warehouses, emails, CRMs, ERPs, CSV, JSON, XML, and APIs. Ingesting this data into a format that your systems can understand and use is no easy task, which is why companies have to utilize dev and data teams to support their data onboarding efforts.

Without the team or tools to manage data onboarding, it's difficult for customers to realize the value of your product. CRMs, inventory management software, ERPs, and product lifecycle management software all need clean data coming in to execute properly.

Even if data is successfully imported, the lack of standard formatting renders a lot of it useless. Your operational system can quickly become riddled with errors, inaccuracies, duplicates, etc. when data isn't formatted or validated before being ingested.

Familiar problems

Imagine your company is onboarding customer data via CSVs. Let’s say your customer’s CSV has a field called "PO #," but your schema requires a field called "Purchase Order No." The data won't import properly due to the different schemas, and without validations someone from your team must manually transform the data before it’s ingested.

Dev teams attempt to solve these recurring data onboarding problems by dedicating extra hours toward data wrangling, creating in-depth documentation for non-technical teams, and/or building and maintaining in-house solutions.

Unfortunately, these solutions cause further downstream problems. 

  1. The more custom scripts and glue code you build, the more people, time, and money you'll need to maintain each solution. Devs grapple with formatting errors, custom scripts, and maintaining APIs and building connectors. 
  2. Companies struggle to scale in-house data onboarding solutions as the company grows. Custom data uploaders require constant tweaks from technical teams to handle the multiple data importing scenarios, files, and formats.
  3. Digging through documentation is cumbersome for customers and internal teams who want to quickly upload their data. That’s assuming you even have documentation that’s up-to-date and clearly written.

Throwing more internal resources to manually onboard customer and partner data is a losing game—the high cost isn't worth the small bump in efficiency. Having developers and engineers to fix bugs and wrangle messy data takes away resources for investing in new products or technology.

Costs

People make mistakes, even highly-trained engineers, developers, and data scientists. But errors made during data onboarding cause headaches for internal teams and customers. Manual data wrangling demands meticulous attention to detail and the ability to sort through thousands of fields to select and correct errors. 

Data onboarding difficulties lead to several major issues: error-prone data, high data-wrangling costs, frustrated internal teams, and a sub-par customer experience. 

Take a second to consider how costly manual data transformation is for companies. The nationwide average salary for a software engineer is just under $120,000. That number jumps to about $160,000 in San Francisco and $130,000 in New York City and Seattle. If the average company employs a team of 10 engineers who spend 45% of their time on data wrangling, it costs upwards of $540,000 per year on data cleaning.

If a highly-technical team can focus on product work, it's bound to drive a business forward. New product features, incredible functionality, innovative software, and a delightful customer experience can take place when teams aren’t bogged down with data onboarding tasks.

Most importantly, internal teams have the time to provide an excellent customer experience. A study by Gallup revealed that companies that successfully engage B2B customers realize 63% lower customer attrition, 55% higher share of wallet, and 50% higher productivity. 

Engaging customers has clear benefits, but it also shows you respect your partners' and customers' time. Since data onboarding is one of the first touchpoints a company has with customers, it's the perfect opportunity to delight and impress with a quick, simple experience.

Osmos’ approach

Although companies can't avoid messy data and convoluted formatting, they can use technology to simplify and improve their process. Let's look at three common scenarios where Osmos' data onboarding solutions can have a positive impact.

  1. Companies want to provide a self-serve data onboarding experience for their customers and partners.
  2. Companies want to provide a self-serve data onboarding experience for their internal teams to upload data on behalf of their high-touch customers or partners.
  3. Companies want to automate customer and partner data imports in order to bring in cleaner, fresher data on a recurring schedule.
Customer data needs to be cleaned before onboarding is complete. That's where Osmos can help.

Using Osmos' dev-friendly solutions, both technical and non-technical teams can tackle the most challenging parts of the data onboarding process—data transformation. Osmos Uploader and Osmos Pipelines are simple to customize and scale, so your team can quickly onboard customers with both small and massive datasets. 

1. Osmos Uploader - enable your dev teams to quickly a build a smart data uploader and embed it into your product or web property. When a customer or partner needs to share data, they simply click the upload button. This brings them to the Osmos Uploader interface, where they can clean and map data without having to write code. In just a few clicks, our no-code data transformations help them upload their data so it matches your system's schema. It's the easiest way to empower end-users to send you clean data, every time.

2. Osmos Pipelines - turn one-time data onboarding into automated data relationships. They enable your internal teams to pull data from a Source Connector (file stores, databases, apps, APIs, or emails) and automatically clean and validate the data before sending it to the Destination Connector. You can set them up to run on a recurring schedule or manually trigger them at any time. There's no need to worry about having the most up-to-date data when it's automatically ingested into your operational systems.

Powering Osmos products is a real-time, AI-powered data transformation engine that lets end users easily teach the system how to clean and map data with QuickFixes, AutoClean, formulas, and column mapping.

  • QuickFixes are one-click, data-cleanup buttons that allow you to easily clean up your data for the most common scenarios for that data type (ie. Date, Text, Numeric etc.). You can combine multiple QuickFixes to both cleanup your data and resolve errors easily.
Osmos QuickFixes for data onboarding
  • AutoClean is simple to use AI-powered data cleanup that learns and detects a pattern from examples of the clean data. Involves transforming your input data by providing examples of the clean data in the output column. 
Osmos AutoClean for data onboarding
  • Column mapping is used to directly map a single source column (from the left table) to a single output column (in the right table). Column mapping is useful when the source data in a specific column doesn't need to be transformed or cleaned up, just mapped to an output column.
osmos column mapping for data onboarding
  • Formulas are used to complete complex transforms on data from one or more input columns. We have several predefined formulas (such as CONCAT, DATE, ADD, IF, IFERROR etc.) that can be used together.
osmos data transformation with formulas
  • Validators - Ensure uploaded data is correctly formatted, mapped, and ready to use every time.
osmos validators
Simplified data onboarding experience will become the standard, as companies adopt no-code technologies and prioritize the customer experience.

As more companies adopt no-code technologies, customer expectations and business growth opportunities will inevitably reshape. Now is the time to eliminate your data onboarding challenges with Osmos’ dev-friendly solutions designed for non-technical end users.

Bring in newer, cleaner, fresher
external data

Try Osmos for free

Katrina Kirsch

Marketing