7 Questions to Ask When Evaluating Business Intelligence Software

The Quest to Become Data-Driven

The stakes to transform into a data-driven business have never been higher. From the sales floor to the C-Suite, every department wants to use data to its advantage. 88% of executives say [1] they feel the urgency to invest in big data initiatives — and it makes sense. Companies that embrace analytics and business intelligence (A& BI) continually outperform those that don’t. Data-driven companies are 23 times more likely to acquire customers [2].

Companies that embrace analytics and business intelligence continually outperform those that don’t.

The shift to embrace data has led to record A& BI spending. 55% of companies report investing $50M or more into big data initiatives [1]. No matter how large your BI budget is, choosing the right software is crucial to your success. But let’s face it: The business intelligence software landscape is gigantic. With hundreds of vendors out there, knowing who to evaluate and what to look for in a solution can feel overwhelming.

The BI software vendor landscape is gigantic, ranging from new entrants to megavendors.

If you’re starting to evaluate software, you may be unsure where to start. What’s the difference between all these BI software vendors? Which capabilities and features are important to have? How should you approach the process? What’s changed since your last BI purchase?

In the following pages we explore the top 7 questions every company should ask during the evaluation process — and break down some of the top BI trends and features to consider along the way.

A Brief History of
Analytics and Business
Intelligence Software

A Brief History of Analytics and Business Intelligence Software

If you’re new to the world of business intelligence, or revisiting after a hiatus, it’s helpful to have a solid background of where we’ve been — and where we’re headed.

Dashboards reigned supreme

Business intelligence has historically focused on tracking and curating data, usually in the form of dashboards or reports. Early BI tools were designed to surface high-level insights in dashboards on a scheduled basis, but lacked real-time reporting capabilities.

These dashboard-focused tools usually answered pre-determined questions executives raised in advance. If questions changed, or additional information was required to make decisions, the dashboards needed modification. Only technical people with knowledge of SQL or other coding languages could build them, which was handled by a member of the data or IT team — effectively making them the data gatekeepers.

On-prem constraints stunted insights

In the past, implementing a business intelligence solution meant building an on-premise data center and hiring an army of IT talent to manage it. Because data storage and compute was relatively expensive compared to today, data analysis was limited.

Outdated data was often deleted to save on massive storage costs, preventing long-term historical analysis. Computing and resource constraints, combined with business teams’ inability to dig into the data behind these dashboards and reports, limited ad hoc analyses to situations when it was absolutely necessary — leaving many questions unanswered. And without the ability to ask those questions on the fly, mission critical insights remained hidden.

What’s Changed?

The datasphere looks very different today. The volume, variety, and velocity of data produced is unparalleled. Thanks to the internet, mobile devices, and the Internet of Things (IoT), more data gets created and collected than ever before. In the time it takes to walk to the water cooler and back, more than 3.8 million queries are submitted to Google and close to $1M is spent online [3].

We now live in a data economy

The velocity and volume of data shows no signs of slowing down. IDC expects the global datasphere to surpass 175 zetabytes by 2025 [4]. The pace data and customer needs change in today’s business environment requires the right tools to keep up — tools that can provide all employees with real-time access to relevant data and insights.


175zb

amount of digital data generated globally by 2025 [4]

Annual size of the global datasphere

This new data economy is powered by the modern cloud data warehouse (CDW).Modern CDWs collect data from any source and scale elastically to support nearly infinite users and ad hoc analytic workloads. This includes support for unstructured and semi-structured data such as JSON. Storage and compute costs have also come way down, meaning historical data doesn’t have to be tossed, and technology can meet — and even exceed — the demand for insights.

It’s no surprise that analysts expect 83% of enterprise analytical workloads to be cloud-based this year. But despite the wealth of data available and many opportunities to harness it to drive decisions, 73% of companies fail to put it to use [5]. Meanwhile, decision makers can’t access this data or uncover insights in a timely or efficient manner.


73%

of companies fail to put data to use [6]

So where do you go from here? You need a BI tool built to thrive in the new data economy. But how do you know which one to choose?

7 Must-Ask Questions for Evaluating BI Tools

If you’re comparing BI software, we’ve put together a list of questions to help guide your evaluation criteria and ensure you choose the best solution for your business’ needs.

Is the software solution built for cloud
data warehouses?

Why it matters

As you evaluate analytics and BI software solutions, make sure to look at cloud-based tools that capitalize on CDW capabilities. Things change more quickly than ever, and teams need real-time data access to make sound — yet rapid — decisions.

Today’s volume and variety of data is much better managed in the cloud — not stuck in a slow on-prem database or sitting in an extract on someone’s PC. That’s why 68% of database market growth is in the cloud[6].

Unfortunately, many companies that have invested in CDWs still use BI tools meant to meet the needs of the pre-CDW era. These solutions fail to maximize the value of CDWs by requiring data extracts prior to analysis, making it difficult to analyze semi-structured JSON data, and presenting other roadblocks that slow down time to data insight.

What to look for

Most analytics tools available today have some form of cloud offering, but few were built for the cloud data warehouse. Seek a BI solution that gives teams direct access to data inside the CDW.

These modern BI solutions accelerate time to business insight by querying data live against your CDW and leveraging the compute power and speed of the cloud to quickly analyze massive datasets in real time. They also capitalize on cloud benefits such as elasticity, real-time data access, sharing, and usage-based pricing.

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