To succeed, every modern company not only has to be a software company, but also a data company. The problem with this is that accessing the needed data is hard.
In the past acquiring needed data and metrics was simple; all business apps were on-premise and used a standardized SQL server. Business analysts were able to work directly with data that came from one source.
Today, business apps are cloud based, and data is moved to data silos. SaaS companies don’t provide direct access to databases for a variety of reasons, from security to competition. This means that data analysts can no longer work directly with data. Instead, there is a lot of work that must be done before the data can be evaluated. This includes manual data export and manual data merging from various sources. These steps have dramatically slowed down data analysis.
Hiring for Data Extraction
To cope with the situation, companies have started to employ engineers to automate data extraction. Moreover, companies pay for using a variety of products from the data stack, such as data warehouses and ETLs.
At the end of the day the costs of this extraction add up to a lot of money.
According to LinkedIn, there are almost 3 million business analysts and some 150,000 data engineers working around the globe today. Yet to work efficiently, business analysts need 20 times more data engineers than currently exist.
Clearly a different solution is needed for this data collection problem.
Automation for data – a better way
The market has responded to the huge shortage of data engineers by launching automation tools to save data engineers’ time. However, these tools still require some additional data processing by the user using Python and SQL.
With Conduit, there is no need to hire data engineers. Our solution enables any business user, including data analysts and CMOs, to prepare data for analysis.
Conduit is focused on four verticals:
- Direct-to-Consumer brands
- Shopify and Amazon merchants
- E-commerce marketplaces
- SaaS businesses
These verticals have a very similar set of third party data silos (Google, Facebook, Stripe, Shopify, etc); customer acquisition costs represent one of the largest expenses, and they have similar KPIs.
The current state in data collection is cumbersome, expensive, and requires too much manpower to be efficient. A new way to collect and analyze data is here, and it will change the way you do business for good.