Executive’s Guide to BI Tools

 

CEO Josh Miramant

Blue Orange’s Opinion:
“It’s a clear industry leader. Full-featured and capable, but with a healthy layer of bloat. Similar to PowerBI, it’s offering a lot and that comes with complexity. Their dashboard style customization is poor. They also break their product up into confusing tiers, dragging you into upgrades opaque pricing. One example is the Tableau Server vs using custom data patterns. It can be slow with big data volumes. On the positive side, their dashboards are flexible and intuitive. ”

Tableau – Pros

• Usability: Tableau Desktop endeavors to do more than make charts, but rather to show “live visual analytics.” A slick interface with drag and drop buttons allows the user to quickly be able to spot trends in the data.
• Connectivity: There is a lengthy list of supported data sources, including Microsoft Excel, Google Analytics, Box and PDF files. Tableau enjoys the ability to connect with pretty much any type of database, as well as use a whole range of data blending options, to output into an even bigger selection of charts. Dashboard visualizations can be easily shared, and are mobile-friendly. The package supports establishing connections with several information sources, like HADOOP, SAP and sound unit Technologies, that improves information analytics quality and allows the making of a unified, informative dashboard. Such a dashboard grants access to the desired info for any user, even on their mobile.
• Ease of Use: The tool’s intuitive manner of making graphics and an easy interface permit non-dev users to utilize the fundamental app’s practicality to the fullest. Users organize data into catchy diagrams in a very drag-and-drop method that facilitates info analyzing and eliminates the necessity for the assistance of an IT department for pattern building. The strong community forum then fills the gaps and allows users to share their expertise and experience.
• Highest Performance: Apart from the Tableau’s high visual image practicality, users rate its overall performance as strong and reliable. The tool conjointly operates quickly even on huge information.

Tableau – Cons

• Expensive: Tableau Desktop becomes an expensive option for a single user as it costs $70 per month that is billed on an annual basis, making this more expensive than other competing solutions after the free trial offer. On balance, it also includes the associated application of Tableau Prep under the Tableau Creator package.
• Usability: Too Complex. On one hand, the tool provides best-in-class info visual interpretation with limitless potential, on the other hand its reporting capabilities require extensive time and resources to train employees on correct preparation, implementation, and maintenance. Several operations need the creation of SQL queries, that are not possible without the services of a talented developer. Untrained business users will not be as effective without the out help of IT.
• Connectivity: The software’s potential to integrate endlessly, comes with security problems, embedment problems, and has restricted capabilities for result sharing. [3]

3. QlikView

 

 

https://www.qlik.com/

QlikView is an all-around analytics solution, complete with advanced reporting and visualization tools as well as hands-on data analysis opportunities. It is based on an in-memory data storage engine that can integrate multiple big data sources and can be deployed either in the cloud or on-premise. It offers extensive support for scalability and integration with other Qlik services, which makes it the “analytics solution that evolves with your business.”

 

CEO Josh Miramant

Blue Orange’s Opinion:
“This was my favorite tool to work with until I worked with Looker. QlikView is the most intuitive to build dashboards in and loading data is very smooth. I like QlikView but find the rest of the tools clunky and over engineered. As with most of these tools QlikSense leaves lots to be desired on record linkage and aggregation building. I now prefer PowerBI or Tableau, but QlikView is a whole other thing. It can get sluggish with large data sets.”

QlikView – Pros

• Associative Engine: Advanced data preparation and connectivity allows you to explore data from various angles and to gain new unexpected insights ad hoc.
• Visually highlighted dashboards. Dashboards and guided analytics are visually highlighted for the user during the data exploration process
• Developer’s platform offers customers the ability to extend QlikView with other products from their portfolio and various tools and resources are provided for developers.

QlikView Cons

• Learning curve
• Dashboard not comprehensive[4]

4. Sisense

 

 

https://www.sisense.com/dashboard-examples/supply-chain/

Sisense introduces itself as the “end-to-end BI solution”. On the back-end side, it enables advanced data cleansing, transformation pipelines, and analytics algorithms to be built on top of various data sources. This brings additional flexibility in the way data is being handled, which goes beyond the simple visualizations (but may also require expert knowledge). On the front-end side, it enables business users to create visualizations and quickly spin up reporting dashboards. The Sisense ecosystem can also be extended with 3rd party tools and integrations, which makes the tool available for a wide range of business use cases.

Sisense – Pros

• Rapid deployment
• Incorporates AI
• On-premise and cloud-based option.
• Sisense works well with large datasets using a columnar database approach without requiring very expensive hardware.
• Sisense’s Elasticube™ allows users to take data snapshots.
• Dashboards provide users with good widgets, varied chart types, and informative KPI and metrics views.

Sisense – Cons

• The Elasticube™ isn’t that user-friendly. It’s difficult to create for the average user and requires a lot of technical expertise. In many cases, users must write SQL code, even though Sisense promotes its “codeless reporting.”
• Drains your power, space, and some of your most precious resources i.e. time and money to set up, configure, and coach staff.
• Dashboards are only interactive on the web and are not shareable, which amplifies the disappointment that you can’t schedule reports that can be sent via email.
• Opaque pricing: Sisense doesn’t publish its pricing on its website anymore, so prospects don’t know how much Sisense’s software costs without contacting them. [5]

5. Tibco Spotfire

 

 

TIBCO Spotfire® is a data visualization platform that utilizes predictive analytics. In addition to data viz, it includes data-wrangling capabilities, predictive analytics, location analytics, and real-time streaming analytics.

Blue Orange’s Opinion:
“We had a client request Tibco Spotfire for an app which deals with patients’ chronic health issues. Our embedded Jasper reports provided insights to care providers. Through that project, I decided that I’ll only use it if I must. I don’t like much about it. It’s capable but opinionated. Their in-memory data processing is much less than necessary. It has clunky APIs and their versioning and documentation is a mess.”

Tibco Spotfire – Pros:

• Exceptional response
• The server is easy to manage.
• Single sign-on works seamlessly.
• Visualizer.js is strong.

Tibco Spotfire – Cons:

• Not as glossy as Tableau.
• Poor API
• Lacks training and support materials. [6]

6. Looker

 

 

Looker offers a cloud-based BI platform that is most suited for building analytical applications. Native support for cloud analytics databases enables engineers to explore and (re)model data before exposing it to further services and applications. The looker blocks – pre-built (yet customizable) pieces of code – allow a quick start with different analytics tasks. However, the lack of a point-and-click approach to data modeling may limit the adoption of the tool to organizations with an in-house IT department. They were acquired by Google in 2019.

Blue Orange’s Opinion:
“I love the ease of Looker compared to the bloat of a number of other tools. They have great embedding and template configurations. A close leader with Qlikview, it’s very simple for us but can run into performance issues with big data. It’s also less flexible compared to Tableau or Power BI but this can be it’s benefit. It does most things better and the edge cases are harder to customize for. It focuses on the BI UI and not the data provisioning as much as others, for that reason it’s a great tool to layer on top of a data pipeline. This is my favorite tool in most cases. The biggest downside is the price. It’s a premium product and they price it as such.”

Looker – Pros

• Usability: Provides data modelling language which helps users study the relationship between different datasets.
• Accessibility: The handsome reports, graphs and charts can easily be made and instantly shared via e-mails, URLs, and saved on the cloud.
• Robust: It supports more than 25 types of data like SQL, Hive, Vertica, BigQuery etc. Playful discovery of data sources, layers, and data manipulation.
• Compatible with Mac OS and Windows.

Looker- Cons

• Difficult to share data with 3rd party users.
• The pricing is somewhat high, but if you are a larger company it might be worth it.
• Lacks visualization options and enhanced capabilities with scheduling reports.
• Learning curve for how to work with development and live versions of the models. [7]

7. Domo

 

 

Domo is the modern analytics platform that offers rapid deployment of intuitive dashboards and is mostly targeted to non-technical users. It offers the Magic ETL drag-and-drop which is an example of a simple & intuitive, yet powerful data transformation tool. The ease of use has turned Domo into a popular choice for deployment in business lines in isolation from IT. However, since the platform can only be deployed in the cloud, it lacks the offline analysis feature, which may be incompatible with some organizations’ business models.

Domo – Pros

• Intuitive Dashboards: This BI tool consolidates different data sets into a single easy-to-read dashboard with drop-down menus separating individual visualizations.
• Automatically suggested BI Visualizations: Go from raw data to charts, graphs, maps, etc., with automatically suggested visualizations. You can refine the data, annotate for further commentary or discussions, or refine and control who has access to it.
• Database Connectivity: Drag-and-drop Magic ETL tool enables you to prepare your data with basic to no SQL. Generate multi-dataset reports in a single graphic visualization from a range of database sources securely and easily.
• Advanced Analysis: Your Data Scientists are aided by Domo’s AI engine to utilize artificial intelligence, machine learning, natural language processing, etc, to alert and notify about changes in KPIs or create predictive models.
• Support: Domo’s open cloud platform is an ecosystem of pre-built apps(or build your own and share it), connector APIs and dashboards.
• Mobile Access: The platform offers a native mobile app that offers access to everything you can utilize on the desktop site.[8][9]

Domo – Cons

• Domo is not built for newcomers as the learning curve can be steep, but they do offer training, therefore, be prepared to learn.
• Expensive and Nontransparent Pricing: Assume it’s the most expensive solution on our list, according to the available information on the web. [8]
• Does not support all SQL queries
• Does not fetch real-time data in reports
• Does not offer functionalities such as dashboard creation and OLAP
• Limited functionality with respect to pivot reports
• Users cannot save filters on cards or collections. A new page or subpage has to be created each time there is a card or group for the same filter condition [9]

8. Google Data Studio

 

 

Google offers a no-charge option for visual analytics: Google Data Studio, suitable for both advanced and basic use cases. It gives users the opportunity to collaborate (similar to Google Docs) while building data-reports and takes away all IT provisioning worries since it all happens on Google’s secure platform. The seamless integration with other Google services like BigQuery ML and BI Engine makes it a viable choice for building end-to-end cloud BI solutions.

Blue Orange’s Opinion:
“Good for rapid prototyping and internal dashboarding. Its best feature is its deep integration with GPC (BigQuery and BI Engine). It’s not really on the same playing field as the others so I’ll leave it brief.”

Google Data Studio – Pros:

• Customize colors, fonts, size, labels, and borders in charts and graphs, then drag and drop into reports that match your brand.
• Unlimited data, unlimited pages and metrics with handy features like summary subheadings, easy search, and integrated comments or notes.
• Effortless sharing and speed, akin to what you’d expect out of google.
• Embed Dashboards into HTML environments by simply copying and pasting the iframe snippet.

Google Data Studio – Cons:

• Reports shared online aren’t editable, read-only.
• Can’t manage timing frequency of automated reports.
• Charts and reports can only be from one data source at a time. No data blends
• Developer resources will be needed to automate the data prep and import.
• Connects well with other google products to mostly work with marketing and social media data. Other data will have to go through google sheets, which will require a developer.
• Limited and average customizable visualizations. [10]

9. Amazon QuickSight

As one of the top cloud service providers, Amazon also offers cloud-based analytics and a fully managed BI service: Amazon QuickSight. It is possible to seamlessly access data from underlying data lakes (which, in our opinion, are crucial for modern predictive analytics) and to leverage machine learning models provided by SageMaker. The powerful and scalable calculation engine is the foundation stone of a robust BI architecture while the “pay for what you use” pricing model brings organizations important competitive advantages.

Amazon QuickSight – Pros:

• Usability: Easy integration with one of the world’s leading databases, AWS, and other non-AWS data sources is the real winner here. This lightweight and serverless BI tool can be used for clever and niche dashboards.
• Price: Only paying for what you use is very cost effective.
• Usability: Good for creating basic reporting by the business user. Start getting your business insights immediately.
• Performance: Optimized storage method for fast reporting which can be shared across all users in the account.

Amazon QuickSight – Cons:

• Basic: You can not use it as a primary reporting tool as many of the features are missing.
• Usability: For complex business reports, users need the help of an IT person.
• Access: Sharing reports to other environments or with a 3rd party user is complex.[11]

10. Chartio

 

 

Chartio joins the list of lightweight BI tools with a simple mission statement: make data accessible to everyone within an organization. Data access, exploration, transformation, and visualization are all possible via intuitive drag-and-drop interfaces (it even has a visual SQL builder). While some of the functionality may be lacking for power SQL users, the reduced implementation times might be an important advantage for organizations that require agile data insights.

Chartio – Pros:

• Dashboard: A very organized way of tracking data and trends for your company
• Support: Great customer service
• Usability: Flexible and relatively easy to use without SQL skills
• Integrations: It integrates with Segment, so it can pull in data from many other products/platforms.

Chartio – Cons:

• Layout outdated
• Sometimes some of the pages/reports were a little busy.
• Creating dashboards is easy to do, hard to make look good.[12]

 

11. Metabase

 

 

Looking for an open-source BI solution? Metabase is a lightweight yet powerful tool that is optimized for self-hosting (i.e. easy to install, upgrade, and maintain) and thus allows an organization’s analytics workload to live close to its data. With an upcoming cloud version already announced, the deployment options will cover a wider range of business requirements. While no SQL knowledge is required for advanced reporting, some extra tech efforts might be needed for tuning slow data warehouses and optimizing a large number of queries.

Metabase – Pros:

• Clear and intuitive visualizations
• Free and open-source with an active developer community
• Multiple ways by which you can set up Metabase on cloud platforms
• Variety of databases you can connect to
• Reminders, or “pulses”, that can be programmatically sent out.

Metabase – Cons:

• Local version to quickly get up and running is only available for Mac
• Inability to create complex questions without the use of MySQL
• No”plug-and-play” connectors you can easily use to integrate data from a SaaS system
• Need to do some data mapping to get started. [13]

 

Which BI tool for your business?

Picking the right BI tool for your business doesn’t have to be a daunting task! Get expert help picking the right one for your company with Blue Orange Digital, which has just been listed as one of the top software development companies in New York. At Blue Orange Digital, our mission is to help companies get a grasp of their data and make it do the work for them. We have vast experience setting up data-centric architectures and implementing modern analytics solutions.

Overwhelmed?

You’re not alone. Many companies we speak with are still developing their BI strategies. The good news: you still have great opportunities to build an advantage with your data. The bad news: your staff may not have the skills and capacity to execute a modern data strategy. Contact Blue Orange today to discuss your data opportunities.

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