Dataddo Launches Free Data Integration Plan with No Extraction Limits
Dataddo, the vendor of a no-code data integration platform, has announced the launch of a free plan with no extraction limits.
The company says this plan is meant to lower certain barriers within organizations that can hinder data initiatives, including a lack of employee confidence in data skills. A recent Accenture survey of 9,000 employees across multiple industries revealed that 74% felt “overwhelmed or unhappy when working with data.” There is also a shortage of data professionals, which can leave business users with varying levels of technical skill in the dark.
“What we mean by lowering the barriers is that, with our platform, we essentially allow non-technical people to become data experts–to actually operate what can be called a data integration in a no-code manner, meaning that you don’t actually need to be technically proficient to set up a complete integration flow,” Dataddo CEO and Founder Petr Nemeth told Datanami in an interview. “For instance, you could be from marketing, from HR, or from the finance side, and you still want to work with data. This no longer means that you are required to have some technical background or knowledge. So, this is how we are reacting on this side, when it comes to the deep potential scarcity of [skilled] people.”
Another barrier is the initial investment required to become data-driven, that when coupled with a lack of executive support, can cause data projects to flounder. Dataddo says its free plan aims to make it easier for companies to share data while familiarizing their employees with visualization tools before making a large investment in paid tools.
Dataddo’s free plan offers more than a free trial, as the company claims it is the first free data integration plan on the market that puts no cap on extraction limits. The plan can be used for an unlimited period of time with no pressure to commit.
“We strongly believe that at some point, for every company to be more productive, and to be more efficient, they have to start working with data. And of course, a free trial is great, but it’s limited to typically 14 days or one month. So essentially, you are always forced to make some commitment,” said Nemeth. Though it is an entry-level plan, Nemeth says it will be forever free in order to give companies the option to stay where they are or grow into the paid tiers as their data integration needs grow.
Aside from no extraction limits and an unlimited timeframe, Dataddo’s free plan gives subscribers access to any 10 of the over 200 data source connectors the company offers. The company says its multitude of connectors automate the synchronization of any volume of marketing, sales, financial, and other cloud data to up to three dashboarding applications and/or Google Sheets weekly. Also, the company is able to quickly add new connectors, as it recently built a MongoDB connector for a client in 10 days due to the platform’s efficiency.
The Dataddo free plan is not just for non-technical users, as data engineers may find it useful as a sandbox environment for testing data models. Engineers can test the validity of their models on a small scale before fully deploying them in a data warehouse, helping to avoid the high costs associated with making any changes once deployed.
“With our free plan, you don’t actually need a data warehouse. So you don’t have to invest in the data warehouse part. Even if you’re a larger organization, it’s like a sandbox environment, where you can deploy your data models and let them be validated by your colleagues. If somebody wants to make changes, [the model] has not yet been committed to the data warehouse. But once it is approved across the organization, it can be easily transformed into the full production environment,” said Nemeth.
Advanced users may also be interested in two other features the company is rolling out. The first is reverse ETL capabilities, a feature for which Nemeth saw strong market demand in the past few quarters.
He gives an example use case: “Imagine that you have a list of customers in Salesforce, and you want to create a sort of complex scoring mechanism about each customer. Typically, CRM systems do not support that. So you extract all the data about the customers, then you can extract more data from public data, or it could be data from social. Then you compute the score in the data warehouse, and you can then send back the score to Salesforce or to any CRM system. This is how this particular workload is getting popular. We are at the moment supporting most of the world’s popular CRMs like Salesforce, NetSuite, Zoho CRM, and others.”
The second new feature being released is a headless version of the Dataddo platform that allows users to build applications on top of the Dataddo API. Dataddo Headless is intended for integration-heavy use cases, and Nemeth says it will allow companies to completely free their engineers from constant changes to the APIs of cloud apps, scalability issues, and service-specific implementation challenges. For those wishing to build their own applications, data ingestion can be time and coding intensive.
“Anybody who wants to build their own data product, they can use our data integration technology as a part of their product through the API, without actually spending hours or tons of developers’ time building the integrations by themselves.”
In addition to the new free plan and Dataddo Headless, the company offers two scalable paid plans: Data to Dashboards and Data Anywhere. “The former is a fully-fledged version of the Free plan; it allows subscribers to sync data to more than three visualization tools, and unlocks more platform features and direct support. The latter additionally enables subscribers to send data to warehouses, between warehouses, and from warehouses back into apps (reverse ETL),” the company said.
Dataddo was founded by Nemeth in Prague in 2015 and is now headquartered in Mountain View, California. Dataddo seems a fitting name for this data integration platform, as it is a portmanteau of ‘data’ and the Latin word ‘addo,’ which means to add or join.
As for what’s next, the company plans to increase its focus on data quality. One future capability to watch for is anomalistic data detection, a feature that can check for issues with data already in pipelines and notify users when a data anomaly is detected before a chain reaction of error-based decisions is initiated.