Business intelligence and doing more with data

By William Smith
We look at the trends and challenges, such as trust, facing businesses as they seek to utilise business intelligence solutions and do more with data...

While business intelligence is a term that precedes the digital revolution, having been used as early as the 19th century, it’s clear that big data approaches have supercharged the practice.

According to a report from Mckinsey: “Organisations now have troves of raw data combined with powerful and sophisticated analytics tools to gain insights that can improve operational performance and create new market opportunities. Most profoundly, their decisions no longer have to be made in the dark or based on gut instinct; they can be based on evidence, experiments, and more accurate forecasts.”

Challenges remain, however, with business intelligence tools requiring money, time and expertise to implement, and functioning best if data is easily accessible and not siloed, as is so often the case.

It’s worth, then, taking a closer look at three of the premium business intelligence offerings to pick out some of the trends in the space.

Oracle Business Intelligence

Multinational software company Oracle offers a suite of enterprise technology, but is perhaps best known for its database solutions. Founded in 1977 and based in California, Oracle’s business intelligence is part of its analytics software offering, boasting machine learning integration for automation and prediction. Also including visualisation and collaboration capabilities, the software is integrated with the company’s wider Oracle Cloud Infrastructure. Oracle frames business intelligence as being a critical competency for companies to possess, for both optimising performance and streamlining functions. The company emphasises the capacity to tell stories using its data visualisation features, in order to better interrogate the data on offer.


Purchased by Salesforce at the beginning of August 2019 for US$15.7bn, software company Tableau was founded by researchers from Stanford University. The company has a reputation for the quality of its data visualisation capabilities, which can make data more human-readable and consequently drive greater insights. The latest version of its software, Tableau 2020.3, features integrations with SAP’s HANA database, easier license granting and functionality to write to external databases. One of Tableau’s offerings is self-service analytics, intended to allow customers and partners to also make sense of data, provide more clarity and give weight to a company’s claims.

Microsoft Power BI

Among Microsoft’s vast list of products is its data analysis software, Power BI. Focused on business intelligence, from which its name derives, the cloud-based software allows for the visualisation of data, with a focus on collaboration and speed of analysis. Power BI natively integrates with Microsoft’s Azure cloud services, passing in data sources for analysis, and pushes the power of visualisation. In this case, Microsoft says its intention is to democratise a company’s data and create a data-driven culture wherein all stakeholders are privy to the data they need to best do their jobs.

It’s clear to see that making data human-readable is a real emphasis that stretches across these solutions, which drives home the fact that the point of business intelligence is allowing human leaders to make better decisions by truly understanding the company through the data it produces.

But business intelligence is only ever as good as the data you have collected. Faulty data can lead to faulty decision-making, and those faults can intrude from multiple directions. While the data itself might be at fault, also implicated are the biases of the people presenting or receiving said data.

It’s a problem cloud-based data integration and data integrity company Talend has turned its attention to, as Gray Hardell, Senior Manager Solutions Marketing, explains: “To put it simply, the data landscape has become chaos. As data volumes continue to grow exponentially, organisations have found themselves playing catch-up when it comes to the management of this asset – which has led to distrust in the process.” This tangle is having a real-world impact. “It wasn’t until I was on the phone to a group of CEOs that I realised just how much data distrust was hindering digital progression. During this conversation, the CEOs mentioned that they often spent 50 minutes out of a 60-minute meeting debating the reliability of the data, instead of using the data insights to make critical decisions.”

Talend has thus come up with a “trust score” that measures data accuracy based on factors such as its quality, popularity, and client and user-defined ratings to provide a more objective measure and thus engender trust on the part of decision-makers.

“Given the company’s background in data integration, Talend saw a clear opportunity to reconcile these conflicting opinions on data and provide business leaders – and the organisation – with an objective measurement model for determining data health,” says Hardell. “Talend Trust Score does just this by combining the power of automation with human intelligence to complement the user.”

Identifying the ‘five Ts of trust’ of data as thorough, transparent, timely, traceable and tested, Hardell says that: “The benefit of having reliable data, of course, is avoiding these pitfalls. It’s having access to trusted data sets that leaders can use to make important decisions about the business.”

With research suggesting that analytics returns over $13 for every dollar spent, it’s clear that business will persevere with intelligence-based decision making, with the process being eased by solutions that prioritise accessibility and new methods for establishing the trustworthiness of data. 


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