“Why?”

A quintessential question we ask every day, in any context, at any time. And now more than ever, a question we ask of data.

Companies are eager to learn more about customer 360° and get to the “why” of customer behavior. Yet, many SaaS companies continue to leverage antiquated solutions that were originally intended for static data, relational data, and point lookups in time. This disconnect– between what product, marketing, and analyst teams need to ask of their data and what they have access to–is glaring. And even more concerning, it’s an unsustainable solution.

Legacy BI tools make data analysis nearly impossible to run queries across a continuous stream of events without serious performance issues. Without the ability to effectively analyze event data, the types of behavioral analysis teams want to perform are out of reach. These issues only become more prominent as data volume across companies grows.

How can companies anticipate this massive influx of data and scale the necessary infrastructure? 

Scaling infrastructure to support rapid analysis isn’t easy, and many existing tools on the market weren’t designed with scale in mind. In particular, doing so with tools, like Tableau, isn’t easy–and can push the platform’s operation toward a slow crawl. Not to mention, integrating other event data sources, like Salesforce, can be an extremely time-consuming task. For example, integrating slow-moving lists of accounts, deals, and revenue associated coupled with event data across the entire customer journey–including web, mobile, and IoT, can take hours or days, leaving silos of data and questions unanswered.

While Tableau and BI may not be excellent for discovering the “why,” they still are powerful tools relevant to today’s reporting and data needs. Most notably, when integrated with a powerful customer intelligence tool, like Scuba. 

Read to discover where Tableau’s customer insight limitations stifle the “why,” but open the door for a symbiotic relationship with a real-time customer analytics solution, like Scuba. 

3 key drawbacks of Tableau and BI

Tableau and BI shouldn’t be retired just because they lack certain analytics and fast-scale capabilities. They still maintain relevance and necessity in today’s world of reporting and congregating data. In fact, Tableau shines in three particular areas:

• Empowering users with many visualization types and control around style and formatting. 
• Strong reporting capabilities. 
• A convenient "load and go" solution for data sets that are too big for a spreadsheet.

However, Tableau comes with its limitations for truly comprehensive and fast analytics. In today’s digital landscape, there are some tasks that Tableau can’t entirely achieve on its own.

These include the following three drawbacks:

1. 1. Limited in-depth analysis: Tableau provides basic analytics and reporting, but most companies need more in-depth, cross-channel analysis to guide the development and ongoing improvement of their service. It isn’t optimized for time-series event data, meaning many users often struggle outside of basic reporting. If analysts want to visualize analytics with an emphasis on particular user activity and time, Tableau wouldn’t be able to operate within those parameters since it isn’t built for time series data. For example, visualizing anything from churn rates and renewals to troubleshooting load spikes or application logging would not be possible. This also means it’s not well-equipped for behavioral or ad hoc queries.

1. 2. Requires technical expertise and coding: Tableau isn’t always easy enough for business users to handle on their own, and gleaning insights from the tool often requires scarce IT resources. Data analysis and reporting should be user-friendly, intuitive, and accessible to everyone. The DIY solutions within Tableau often require complicated query languages–meaning, teams have to rely on those with strong technical backgrounds to get answers to questions. Inevitably, this kind of bottleneck results in massive reporting delays and puts additional pressure on data scientists and analysts.

1. 3. Trouble scaling quickly and getting insights quickly: Scaling quickly and pulling insights quickly are high priorities for companies across all industries. But, one-off query requests (also known as ad-hoc query) that require SQL place a heavy strain on existing systems. This can make getting answers through Tableau or SQL so slow that analysts are often unable to run critical queries altogether—and operations of even moderate complexity would hang indefinitely. Without the power and scale to efficiently (and quickly) process high volumes of data, relying on Tableau can mean dealing with long delays and unanswered questions. 

Simply put, Tableau isn’t a single-stack solution and can’t live up to the demand for deep analysis, real-time insights, and at-scale data exploration and querying. Then again, Tableau wasn’t built to be an analytics solution, to begin with. This may seem like a dead end, but then again, endings are often new beginnings–or in this case, an opportunity for easy integrations.

Luckily, Tableau can be easily integrated with real-time analytics solutions, like Scuba. 

How Tableau can work in tandem with Scuba

As the old proverb says, “If it’s not broken, don’t fix it.”

While the proverb above may seem counterintuitive–it bears some truth. At least, in regards to Tableau. As a robust reporting tool, Tableau is good at what it does–and there’s no need to reinvent that wheel. What brands do need, and should consider is adding an additional wheel: a strong analytics platform–like Scuba Analytics. Tableau can work in tandem with Scuba to deliver brands better insights, and the freedom to explore data and ask no-code queries.

By integrating with Tableau, Scuba can offer users the following capabilities and benefits:

1. 1. Scuba offloads compute-intensive behavioral queries of time-series data, enabling traditional BI reporting in Tableau and Redshift to operate more efficiently.

1. 2. When it comes to using Tableau for reporting, companies often realize what they really need is an analytics solution to understand the behavior and usage of our service. In other words, they need a tool to uncover the “why.” Scuba is the best option on the market for customer and behavioral analytics on event data at scale. 

1. 3. With Scuba, query times are insanely fast, no matter the scale. Teams can run a query and expect an answer in minutes–not days, weeks, or months. Getting insight right away mitigates the challenge of stale data and stale insights. Moreover, the pre-built behavioral features like cohorts and funnels make analysis simple.

1. 4. Scuba is more secure and stable than homegrown tools. Homegrown tools paired with Tableau are expensive and tedious to maintain, especially if it requires a data warehouse. When integrated with a tool like Tableau, homegrown tools are difficult to manage and constantly update, prone to data security and privacy compliance violations–and could be vulnerable to data breaches, bugs, and glitches. While infrastructure alone for Tableau can be costly, not to mention big investments in training, it still can’t deliver answers to the behavioral questions most companies have. With Scuba, brands can expect a reliable and easy-to-use platform– that meets all compliance standards and regulations.

1. 5. Scuba easily integrates with other tools, including Tableau. By working together, Scuba can help Tableau make the flow of data seamless, paving the way for faster and more powerful insights.

While Tableau can still be used for static reports, Scuba allows analysts to manage fewer of them and spend more time reading insights. That’s because Scuba ingests data in real-time and in its rawest form—giving users the ability to query data directly. This level of granularity cannot be achieved when data is aggregated and summarized in a warehouse, which creates a disjointed, chaotic environment to glean key insights.

Below is an example of Scuba's integration with Tableau:

Scuba: A complete solution to Tableau’s limitations

Tableau has its strong suits and its weaknesses. Indeed, it becomes a better tool with the support and integration of a platform like Scuba. But, on the other hand, Scuba can actually do the job entirely on its own–without Tableau. 

Meaning, Scuba Analytics can be a solution and replacement for Tableau altogether. 

Scuba is a single-stack solution for both data analytics and reporting. With lightning-fast time to insights, the ability to scale quickly, and no-code querying, Scuba allows brands to achieve what traditional BI tools can’t do: understand the “why.”

“The thing that we like about Scuba is the ability to see logs instantly which we can’t really do with Tableau.” –Quip 

Scuba’s streamlined full-stack solution is cost-effective–integrating the database, analytics layer, and comprehensive data visualizations into a single solution. 

1. 1. Scuba’s pre-built behavioral analytics features lead to richer analysis that allows brands to perform complex conversion, engagement, and retention analyses without using SQL. Brands can easily combine features like cohorts and funnels with a single click to unearth insights they’ve never had before on how users interact with a brand’s services.

1. 2. Scuba’s speed at scale allows brands to leverage 100 percent of raw event data without the need for aggregations or summarizations. Queries can complete in seconds, allowing teams to iterate through questions in minutes.

1. 3. Scuba’s visual, interactive, and intuitive interface enables multiple teams to run their own analytics. They are able to ask simple or complex questions without any special behavioral analytics training or waiting for analysts or data scientists to build reports.

1. 4. Scuba enables brands to create highly specific queries, with customized metrics, to generate insights particular to their business and to support data-informed decision-making.
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3. Dive into your analytics with Scuba

Uncovering the “why” to every single question will never be possible–but in the data analytics world, brands have that possibility with Scuba. Traditional BI tools weren’t built for evolution, despite their ability to adapt and integrate. 

With Scuba Analytics, there’s no need to modify, build, or rebuild data analytics tools. Scuba’s real-time customer intelligence platform provides teams with seamless data exploration, visualizations, and deep insights into the most granular customer journeys.

Want to learn more about how Scuba can improve your reporting and analytics? Request a demo today or talk to a Scuba expert.