Are you considering an all-in-one data analytics solution like Domo? A word of caution: you can move your data into these platforms but can you get it out?
Data is the currency that powers your business and, in many cases, is the lifeblood for making money and selling products. Meanwhile, being able to visualize your data allows you to access it in a way that makes sense and is actionable. Data visualization platforms such as Domo and Sisense offer one-stop shops for all your data visualization requirements. The “we can do it all” feature sets are really tempting. You just load in your data and within minutes to hours, you have your first visualizations. You never have to worry about managing your warehouse, backing up your data, or solving connectivity issues.
“Over the past 8 years, we’ve effectively built seven startups in one integrated platform to meet the dynamic needs of all organizations, no matter what stage they are in their digital transformation,” said Josh James, Domo CEO.https://www.domo.com/news/press/domo-named-one-of-the-fastest-growing-companies-in-north-america-on-deloittes-technology-fast-500-for-second-consecutive-year
“This is really seven startups in one,” Domo’s CEO also told Mad Money’s Jim Cramer in December. Think about that: it’s telling. It’s so hard to execute as a single startup never mind seven at once. Customers who pick Domo are going all-in on a single platform.
Alternatively, you could choose a more modular approach to your analytics stack. This would allow you to pick the best performing tools for your specific use cases and build a flexible foundation for building your analytics.
First you would pick an independent data warehouse such as Snowflake, Redshift, or BigQuery as part of a build-it-your-self approach to creating a full data analytics stack. You are then responsible for finding an ETL tool (such as Matillion, FiveTran or Stitch) to connect your data sources to your warehouse, and separately you need to select a visualization tool such as Looker or Chartio that sits on top of your warehouse. But the key point here is that your data lives in a warehouse and is separate from your data visualization platform.
Okay, so all-in-one or modular? This is kinda a big choice. You are probably feeling like you don’t have the time or the IT staff to get this all plumbed and working and so you’re just going to go with Domo or Sisense because they have it all figured out. So this blog post a word of caution: you can move your data into these platforms but can you get it out? This is a serious question. It’s a bit like Hotel California where you can check out any time you want but you can never leave.
Let’s consider what I mean by that. Domo offers over 600 connectors so you can get your data from almost any source into Domo. But there really isn’t a single connector for getting data out of Domo. Not from Stitch, not from FiveTran, not Matillion. Why? Because it’s not possible. You can connect your data from Snowflake, Redshift, or BigQuery to Domo, but it’s going to create a copy of that data and store it in Domo’s internal database. Then let’s say you have streams of data coming from other sources such as Google Analytics or log data that comes into Domo as a firehose. You stash it all in Domo and make some beautiful dashboards. Domo ends up being your source-of-truth data warehouse for your business.
But now let’s say you decide you want to move away from Domo because of pricing or features or some other reason. How will you get your data out? Yes, you may have copies of that data elsewhere in their original source, but you may not. Can you point Looker or Chartio at your Domo database? No. Are there tools that can quickly extract data from Domo and move it to another warehouse? Not really. Domo provides an API for querying data but it’s not exactly a way to move gigabytes or terabytes of data out. There are numerous reviews of users struggling to extract data from Domo. But at the end of the day it’s the ultimate vendor lock in that no one is talking about.
Sisense takes a similar approach with their ElastiCubes. It’s their own data warehouse technology, that while fast, is completely proprietary. It seems even Sisense has realized that this approach won’t fly because they recently added the concept of Live Models with Sisense Live Connect (a much better approach).
Just last week, we used Matillion to move a dataset from BigQuery to Snowflake. Both are open technologies with an ecosystem of connectors in both directions. It was a simple task. If you wanted to switch from Chartio to Looker or vice versa, each of those tools provides connectors directly to all of the major data warehouse providers. You are able to choose, change my mind and choose again, and continue to select the technologies that are best for me at any given time or project.
There are a lot of reasons why you should care about where you put your data:
- When a vendor has your data, they have you locked in. They know it’s hard for you to move so they can raise prices whenever they want, take their time with new features, and just in general hold you hostage.
- Choices create competition and competition drives features and security. Snowflake, RedShift, and BigQuery are all competing against each other to be the best data warehouse. Because it’s so easy to move and because they all have a pay-as-you-go pricing plan, they know they have to be the best or customers will move. If one of these platforms had a security breach, you would immediately see some customers extracting and loading their data to another warehouse, as they can easily do. Would you even know if Domo had an internal security problem or if their best practices weren’t so “best”?
- Data Analytics is still a fairly new category, and there are so many platforms out there. Too many. The dust will eventually settle. Just as technology has always done, the best will survive and the others will disappear or be acquired. We just don’t know which ones will survive yet. And as a customer using this cutting edge data analytics technology you should be keeping your options open. That means open interfaces and being able to control your own data.
If you want to learn more about getting starting with a data visualization platform, feel free to contact us at email@example.com.