Domo vs. Power BI vs. Qlik Sense vs. QuickSight vs. Tableau: Self-service business intelligence has become the go-to tool for agile, fluid business decisions.
By Martin Heller
Business intelligence (BI) and analytics platforms are a staple of informatics for medium to large businesses. Visual-based data discovery has been a key component of BI since about 2004; this trend has moved the responsibility for analytics from IT to self-service by business analysts and managers, with support from data scientists and database administrators. The emphasis of BI has changed from generating monthly reports from the system of record, to interactively discovering and sharing trends, forecasts, and answers to business questions based on data from a variety of internal and external sources. Instead of needing months to make a decision, businesses that have adopted self-service visual data discovery can often decide on a course of action in a few days.
How does one choose a self-service BI platform? Mostly, you want to find the platform that is the best fit for your company, both from the point of view of the users and from the point of view of the IT infrastructure.
Does the BI platform match the skills of the people who will use it? Can your people learn and use it easily? Does it make analysts’ jobs easier, or does it create more barriers than it destroys?
Is it able to read all of your internal and external data sources? Can you easily clean and transform your data within the platform? Is the platform able to display all the charts you require? Can you share your analyses with anyone in the company, or only with licensed users?
With these considerations in mind, let’s examine (in alphabetical order) five market-leading BI platforms.
The 5 best self-service BI tools compared
Domo is an online BI tool that combines a large assortment of data connectors, an ETL system, a unified data store, a large selection of visualizations, integrated social media, and reporting. Domo claims to be more than a BI tool because its social media tool can lead to “actionable insights,” but in practice every BI tool either leads to actions that benefit the business or winds up tossed onto the rubbish heap.
Domo is a very good and capable BI system. It stands out with support for lots of data sources and lots of chart types, and the integrated social media feature is nice (if overblown). However, Domo is harder to learn and use than Tableau, Qlik Sense, QuickSight and Power BI, and at $2,000 per user per year it is multiples more expensive.
Depending on your needs, Tableau, Qlik Sense, or Power BI is highly likely to be a better choice than Domo.
Power BI, Microsoft’s entry into the self-service BI fray, includes a web interface to a service hosted on Azure and a Power BI Desktop application for the Windows desktop. It’s much more modestly priced than the competition: A standard account is free, a Pro account is $9.99 per user per month, and the Power BI Desktop is free.
Both the website and the desktop application are updated on a regular basis. The Power BI Desktop is updated monthly; it’s hard to tell when the site is updated.
For some data sources, Power BI has predefined charts, dashboards, and reports. For example, the default Visual Studio Online dashboard and report provide at-a-glance views of Git, pull request, and version control activity across the projects you configure for your account. For other sources, Power BI expects to see certain markers for its data. For instance, it supports Excel Worksheet named tables, Excel Data Model tables, and Power View sheets. If you only have raw data in your Excel worksheet, you need to go back to it and create one or more named tables; it also helps if you make sure your data types are correct prior to import.
Power BI is a reasonable choice for companies that use the Windows, Office, and Azure ecosystem. It’s also a good choice for cost-sensitive companies that want to provide BI to everyone in the organization. On the down side, Power BI does not give you as much analysis capability or control over your charts as Qlik Sense or Tableau.
Qlik had a “Mode 1” or traditional BI product in QlikView, and has expanded to self-service BI with Qlik Sense. Introduced in 2014, Qlik Sense is a do-it-yourself BI and visualization product based on the same in-memory associative data-indexing engine as QlikView. In 2016, Qlik added its reporting engine, previously available only with QlikView, to Qlik Sense.
Qlik Sense 2.0 is a very capable data discovery and interactive analysis tool. It can connect to virtually any SQL database, and it offers a good deal of control over visualizations. However, it is not as easy to learn, as easy to use, or as flexible in the presentation of visualizations as Tableau.
Data import for BI is often a messy process. Qlik Sense 2.0 tries to associate identically named fields in different tables, but also compares the data and makes recommendations about similar fields. This new feature is called Smart Data Load.
Qlik Sense 2.0 also introduced the Qlik DataMarket, a source of public and commercially available data in six categories: business, currency, demographics, society, weather, and the economy. Having public data helps quite a bit when you’re analyzing your private data.
Qlik normally keeps data in memory in compressed form. There are times, however, that you have too much data to fit into available memory, in which case, Qlik Sense can use “direct discovery” mode, which combines in-memory data with in-database data on demand. In direct discovery mode, some fields are loaded into memory only as metadata/symbol tables that can be used in expressions. The actual data residing in the database will be queried as needed.
When working with Qlik Sense, you can save a bookmark to the current selection state of the current sheet, and you can combine bookmarks into stories and add text and other annotations to make the story self-explanatory. If you’re using a story for a live presentation, you can drill down to the source for any visualization to answer a question, then return to the story when you’ve answered the question.
Qlik’s associative green-white-grey experience in which colors of displayed values indicate state (selected-selectable-not selectable) helps you to spot both related and unrelated data without having to dig — a very nice touch. I also like Qlik’s way of defining expressions, but not quite as much as I like Tableau’s. Qlik Sense offers good control over the appearance of visualizations — better than Microsoft Power BI, but not quite as good as Tableau.
Amazon QuickSight runs entirely in the AWS cloud, has good access to Amazon data sources and fair access to other data sources, and offers basic analysis and data manipulation at a basic price. Of the other products discussed here, QuickSight most closely resembles Power BI, only without the dependence on a desktop product to create data sets — or the level of analysis power provided by the Power BI Desktop/Service combination.
Like Power BI, Qlik Sense, and Tableau, QuickSight connects to myriad data sources and lets you prepare data sets. Once you have data sets, you can create analyses with one or more visualizations, which you can organize into dashboards and stories. You can share data sets, dashboards, and stories within your organization. QuickSight makes this process quite easy and straightforward, but it lacks some useful visualization capabilities found in competing tools.
The first user in a company is free forever, and a team trial with four users is free for 60 days. Beyond the trial, additional users cost $9 per month each for the Standard edition or $18 per month for the Enterprise edition.
The first QuickSight user gets 1GB of SPICE (Superfast Parallel In-memory optimized Calculation Engine) storage, and additional users include 10GB of SPICE. Additional SPICE storage costs 25 cents per gigabyte per month for the Standard edition or 38 cents per gigabyte per month for the Enterprise edition. The Enterprise edition adds secure data encryption at rest and a connection to your organization’s AWS Active Directory.
SPICE is QuickSight’s high-performance in-memory data store for visualizations and is required for data imported from files and optional for data in SQL databases. SPICE tables are limited to 10GB each.
For a shop with many data sources hosted on AWS, limited analysis needs, and limited development time, using QuickSight appears to be a no-brainer. QuickSight adds easy analysis and visualization capabilities for a nominal cost.
Tableau describes its products as offering “analytics that work the way you think” and says these tools harness “people’s natural ability to spot visual patterns quickly, revealing everyday opportunities and eureka moments alike.” There’s a certain amount of truth in that, although you could say almost the same thing about many other BI tools.
The visual discovery phase of the analysis workflow is the sexy part, but it’s not where most people spend most of their time. In my experience, importing and conditioning the data can easily consume 80 percent of the time you spend with a BI product.
Now that Tableau can do cross-database joins, you’re likely to import multiple data sources and join them, although you might have most of them hosted in your data warehouse, if your company is big (or rich) enough to have one.
Then you’re going to want to filter and condition your data on a row-by-row basis. Finally, you’ll get to the point where you can actually start creating visualizations, although it’s not unusual to have to perform additional data transformations while you’re trying to do your exploration. But data conditioning and transformation are easily accomplished in Tableau, certainly as easily as they would be in Excel. There is no need to go back to the import stage to add computed fields or filter the data.
Visual discovery in Tableau is powerful and Tableau has set the bar for its easy-to-use implementation and fine control of the chart display. You build a Tableau visualization by clicking on or dragging the dimensions (typically discrete categories or characteristics) and measures (numeric values) of interest, and either choosing a mark (the type of display, such as bars, lines, and points) yourself, or using automatic mark selection, or using the “show me” method for selecting the visualization.
For more control, you can drag dimensions and measures onto specific mark characteristics or “shelves.” When you understand what’s happening in your analysis, you can share dashboards and stories with others. That’s easily done by publishing to Tableau Server or Tableau Online, whether you’ve been working in Tableau Desktop and need to upload, or you were already doing your analysis online.
Tableau pricing has become quite competitive, at least compared to Qlik and Domo. Personal edition: $35 per user per month; Professional edition: $70 per user per month; Tableau Server: $35 per user per month; Tableau Online (fully hosted): $42 per user per month.
I must note, however, that Microsoft Power BI offers something like 80 percent of Tableau’s features for about 25 percent of its price. Whether that calculation holds up when you account for labor costs and benefits to your company is something you’ll have to determine for your own situation.
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