Top 7 BI Tools

Why BI is important, what makes a good BI tool, and our list of the top 7 on the market.

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Top 7 BI Tools

Business intelligence helps companies make decisions based on data, rather than gut feeling. It’s defined as the process of analyzing data for the purpose of deriving actionable insights - ultimately leading to confident decisions that unlock business growth. For growing companies, BI helps track results, manage risks, stay on top of competition, and steer the company ship in the right direction.

While the concept and term have been around since the 1950s, it’s become increasingly relevant - and is now a crucial, non-negotiable part of business strategy - for two reasons.

  1. The value, power, and necessity of data is now proven, which means that every business is striving to become data-driven. Data-driven companies are proven to perform better. According to McKinsey Global Institute, “data-driven organizations 23x more likely to acquire customers, 6x as likely to retain customers, and 19x more profitable.”
  2. Businesses have massive amounts of data readily available in the various existing tools they use every day. It’s sitting in Salesforce, HubSpot, Google Analytics, Stripe, and more. If companies already have this treasure trove of information that's sure to help them hit their goals and strategically grow, it feels within reach to leverage it.

The difficult part, however, is figuring out what to do with it - and how to ensure that the process of turning data into insights is ongoing and scalable. With BI being top of mind for most companies, there's a wide range of sophisticated solutions, both old and new, that can help.

The main issue we see with BI solutions today is that they are heavily in favor of data analysts and data engineers as the sole users. This may make sense in terms of initial implementation, but if we get back to the definition of BI - aren’t we forgetting about our end users? The ones who will actually make decisions and base their work around insights derived from data. Limiting data to highly technical, data-specific folks in your organization means your data team is bound to become a bottleneck, and you’ll inevitably end up with a company-wide data adoption problem. If end users can’t access and analyze data they need, when they need it, the chances of your company actually being data-driven, is low.

With that in mind, here is a roundup of our top 7 self-service BI tools. Our main criteria was 1) robustness of platform, and 2) “self-service” abilities; ease of use for business-users.

Y42

Y42 is a full-stack data platform that’s designed so that anyone can use and run it, offering both no-code and SQL options. It’s developing an industry focus on eCommerce businesses, helping them merge and visualize data from various sources.

Known for:

  • Good support
  • Easy to set up connectors and sources
  • Speed
  • User-friendliness

What people say could be improved:

  • Limited number of integrations
  • Some bugs due to fast development of product

Domo

Domo is a cloud-based “business management” platform that brings all your business data together in one place. It has 1,000+ data connectors, consumer-friendly data visualizations and an environment that doesn’t require coding, making it easy for people to self-serve.

Known for:

  • User-friendliness
  • Fast time to deployment
  • Number of connectors
  • Task Management & real-time messaging features

What people say could be improved:

  • Cost, and having to pay for Viewer licenses
  • Training
  • Time-consuming to build custom reports
  • Larger data sets can be a hassle

Qlik

Qlik Sense is a complete data analytics solution that aims to empower everyone within companies to make data-driven decisions in a timely manner. Their platform also delivers AI-powered insights and suggestions to both analysts and consumers.

Known for:

  • Associative Engine and Cognitive Engine for smart insights and suggestions
  • Flexibility of deployment (on-prem, any cloud provider, multiple clouds)
  • Strong storytelling capabilities with visualizations and dashboards
  • Programs to boost adoption and data literacy for customers (Qlik’s Data Literacy Program & Executive Insights Center helps to align analytics to business goals - closing the loop on the purpose of BI)

What people say could be improved:

  • Proprietary language that needs to be learned
  • Pricing complexity with add-ons

Power BI

Microsoft Power BI’s platform includes data preparation, visual-based data discovery, interactive dashboards and augmented analytics. They have a new “goals” feature that allows collaborative tracking of key business metrics, which, is a win in our books. Unsurprisingly, it aligns well with Microsoft’s suite of other tools like Office 365, Teams, and more, which explains the traction they’ve experienced, allowing them to capture sizable market share.

Known for:

  • Good value - relatively low price considering capabilities and other legacy systems (Looker, Tableau)
  • Plenty of source connections
  • Ability to work with large volumes of data
  • Desktop version doesn’t support Mac, which can cause a data consumption problem from business users

What people say could be improved:

  • Runs only in Azure
  • Formatting and visualization could be more user-friendly
  • Heavy; takes up processing power

Metabase

Metabase is the easy, open-source way for everyone in your organization to ask questions and learn from data. They claim to not require SQL for their explorations, however, it seems that some is necessary to be able to understand and use the platform properly. Metabase does not include the modeling layer.

Known for:

  • Fast implementation
  • Open source is always free, and is an excellent option for no $ investment
  • User-friendly interface
  • Quick self-service analytics (though less robust)

What people say could be improved:

  • No version control
  • Some SQL is required - especially needed for more complicated questions
  • No modeling layer
  • Reporting and visualization is limited on free plan
  • Lack of support and documentation

Whaly

Whaly is an integrated, self-service business intelligence platform that includes data collection (ETL), modeling, and visualization, all in one. Their mission is to grow data adoption and company-wide trust in data by enabling data teams and business teams to work better together. This means their modeling layer is robust and enables analysts and engineers to build models in SQL or through their visual builder, while allowing business teams to self-serve. It has 150+ native integrations.

Known for:

  • User-friendly interface
  • Robust modeling layer in SQL
  • Customized dashboards
  • Speed of load time
  • Fast and responsive support team
  • Push and embed features so people can access reporting in their favorite tools

What could be improved*:

  • Recent player
  • Missing some connectors
  • Lacking certain advanced features

As a recent player, Whaly doesn't have reviews on G2 or Trustradius yet, so this is largely speculative for now.*

Looker

Looker is an enterprise platform for business intelligence and embedded analytics, that was acquired Google in 2019. Looker helps companies explore, share, and visualize their data, to drive better business outcomes. It does not include an ETL, so focuses more on modeling and visualization features.

Known for:

  • Robust modeling capabilities
  • Enterprise-ready with large enterprise customers
  • Self-service consumption is strong (but limited - adding new dimension requires code)
  • Great tool for data engineers

What people say could be improved:

  • Steep learning curve, must learn proprietary language LookML
  • Expensive, particularly for SMB and mid-market
  • Overly complex for business users
  • Time-consuming implementation, training, and set-up
  • Slow load time

Looker is certainly considered a powerful platform (and legacy system, along with Tableau), but beware of certain factors like dependency on strong coding requirements (learning a new proprietary language like LookML), and time-consuming implementation and configuration. This makes collaboration between data teams and business teams more difficult. While self-service consumption is strong for Looker, their configuration is too complicated and technical to be fully self-service.

Let’s not forget BI’s main purpose - going from data to decisions, fast. We shouldn’t lose sight of the fact that the main goal is to deliver valuable, actionable insights to end business owners quickly, for them to make timely actions and decisions. Things like learning a new language, lengthy training time, slowness of loading and API, and limitations for non-technical business users to access data make certain solutions more problematic, despite their strengths as an overall platform.


If you have any thoughts or questions, please email anna@whaly.io. If you want to learn more about how Whaly can help your company, we'd be happy to chat!

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