Many organizations invest time and money into a number of different software tools to handle everything involved in Big Data.
It’s a necessity– what’s the point of compiling so much data if there is no way to analyze and visualize such data?
One great tool that organizations can use to handle their data is Dremio. This platform offers a new approach to data access and overall management. However, the platform isn’t perfect. Many organizations need additional business intelligence tools to really get the most out of what they can do.
In this article, we’ll break down exactly what Dremio is. We’ll also dive into a few useful business intelligence tools that integrate well with the platform.
To put it simply, Dremio is a data lake engine. This tool can be used to liberate data via live and interactive queries that are sent directly to a cloud-based (or on-premise) data lake storage. It is a popular engine that can work well at operationalizing data lake storage, as well as making analytics and data science processes much faster.
A few upsides of Dremio include fast BI dashboarding, fast data migration, excellent self-service, and data integration. However, the platform does have its downsides. The platform can be a bit lackluster when it comes to the visualization of data and reporting power. Because of this, many organizations who enjoy using it might want to look into integrated BI tools to use with it.
When it comes to tools that one can use with Dremio, there are many options available. Any BI tool that can support SQL queries via ODBC can also query Dremio via the Dremio BI Connector. That being said, there are some pretty unique things that one can do in Dremio outside of the standard SQL queries that one might want to look for in a solution, such as support for user impersonation parameters. One might also want to use a tool that does not cache or try to copy data out of Dremio but still does real-time reporting from the Dremio data lake.
Let’s break down a few BI tools that can do these things and more within Dremio, many of which are technology partners with the platform.
This is a fairly common BI tool to use with Dremio. Microsoft Power BI makes it possible for users of Dremio to migrate to the Power BI Gateway, which has its own wealth of benefits. This tool allows organizations to generate reports directly from cloud-based data lakes. With Power BI datasets that are in DirectQuery mode, users can more easily consume their data via Dremio. Microsoft Power BI might be a popular BI tool, but there are some disadvantages worth considering. The user interface can be quite bulky, and the formulas that users can create with new data tend to be rigid. The free version of Microsoft BI also lacks data handling capacity.
Tableau is another fairly well-known BI tool that works well enough with Dremio. This platform does a good job at visualizing data and connecting directly to datasets in Dremio. However, Tableau isn’t all that different from Microsoft Power BI.
That being said, Tableau is great for connecting to live and extracted data sources, even in ever-changing data source environments.
In the context of data visualization for Dremio, Tableau misses the mark in a few ways. It is a notably expensive tool with not-so-flexible pricing options. The platform also might be problematic for businesses that deal with very sensitive information, as the platform does not provide centralized security at the data level. Organizations might also have to invest in very resource-heavy staff training, as the learning curve for Tableau can be steep.
Looker is an embedded analytics BI tool. The platform is web-based, which makes it a bit easier for Dremio users to build their reports and visualization from a large amount of data sources. Essentially, Dremio will run from between an organization’s data sources and Looker for the purpose of simplifying and accelerating how the platform runs analytics.
Users of Looker can gain access to a variety of NoSQL databases and data lakes. The integration of both tools makes it possible to join data between data lakes and relational databases, though it’s worth noting that the initial integration can be quite complex.
There isn’t a lot that makes Qlik so different from Looker or Microsoft Power BI. As with the above mentioned BI tools, Qlik uses Dremio as a data source via ODBC drivers. The Windows-based platform can help users create visualizations of their data, such as charts, interactive visualizations, and analytics. Qlik can be used for local as well as offline use.
While Qlik is great for locating important information across a variety of data sources, it does have its downsides.
App rendering can be slow, and the platform’s data model view does not automatically save layouts. To integrate Qlik and Dremio, one will need the Qlik Sense desktop application and Dremio Connector.
Microstrategy is an enterprise BI application that supports a wide range of data management and visualization needs, such as dashboards, formatted reports, scorecards, thresholds, alerts, ad hoc queries, and automated reports. It can generate multi-pass SQL queries for the purpose of greeting analytical power and reducing the overall amount of data that can be pulled back into mid-tier.
It’s a sophisticated SQL engine with great performance, but it isn’t always ideal for use with Dremio. There are very few capabilities that it usually offers right out of the box, and there are very few canned reporting capabilities as well.
To properly integrate Microstrategy with Dremio, one will need the Microstrategy 10.0+ desktop application and Dremio Connector.
We’re going to be shameless about it now, since this is what we consider the highlight of this article, anyway. The bonus option is DashboardFox, and it can help you use Dremio for your everyday BI needs.
Because of DashboardFox’s real-time querying from data sources, it makes a perfect compliment to a data lake tool such as Dremio.
There are a couple of specific features in DashboardFox that were specifically added to support Dremio, such as:
Dynamic passing of the user login via the Dremio data string so that Dremio inbound impersonation can be used. This is great to dynamically limit users to only the data access they have defined in Dremio.
Support for Dremio data types so that they are automatically detected when building an App in DashboardFox.
Plus, DashboardFox works seamlessly with features in Dremio such as reflections and more.
And of course, you get all the other benefits of DashboardFox, including:
We have a lot more to offer on the table, but to see is to believe, so we are asking you to book a free live demo session with our team of experts. We won’t talk much, but DashboardFox will.
How was our article to the top five business intelligence tools for Dremio?