Tableau made such a splash on the BI market that CRM goliath Salesforce acquired the company in 2019 in what Salesforce CEO Marc Benioff called “the best acquisition in the history of the software industry”. The best BI tools are available across platforms, and because they utilize AI, they're constantly learning and evolving. Today, nearly every medium and large organization relies on BI to make informed data-driven business decisions. In other words, anyone could use Tableau and the more they used it, the more Tableau learned about the type of information users wanted to see. The drop and drag feature allowed users to make queries and provide graphic responses and insights. Tableau eliminated the need for coding with their proprietary technology called VizQL. While it was crude by today's standards, Tableau 1.0 made data palpable to visual thinkers (a.k.a., most people). Tableau 1.0 hit the market in the early 2000s when Stanford students Pat Hanrahan, Christian Chabot, and Chris Stolen released the very first version of Tableau. It added predictive analysis through machine learning, as well as improved visualization with the internet and cloud technology. BI also became more user-friendly and faster. BI tools began adding Enterprise Resource Planning (ERP), which helped integrate, manage, and automate a company's data. Like the internet and the data that is collected, BI boomed in the 1990s and 2000s. While the two engineers had different approaches, both theorized that data could be pulled from multiple sources for full integration and analysis. Then, Bill Inmon and Ralph Kimball revolutionized the BI industry with a dimensional approach to enterprise data analytics. Data warehouses are still a key component of modern data collection and BI.īy this time, there were several BI options on the market, but they could only use the data stored in data warehouses. A data warehouse is a central data repository that compiles data from each department in a company. The term "business intelligence" was coined back in the late 1980s, around the time data warehouses were born. It was difficult to blend multiple datasets, and the charts and graphs weren't exactly collaborative or visually compelling. It was incomprehensible until data scientists made sense of it. For example, the data was prone to human error. Not surprisingly, there were a lot of problems. There was a time in the not-too-distant past when companies collected manually entered data on simple spreadsheets and left it to data scientists to pull some meaning out of the seemingly incomprehensible reports. If you aren't familiar with this data powerhouse, or you know you aren't leveraging Tableau's full capabilities, we invite you to read on. So which BI platform is powerful enough for Verizon, secure enough for Experian, visually elegant enough for Netflix, and fast enough for Ferrari?Īll four companies utilize Tableau, an industry leader in BI software, to inform their data-driven business decisions. That requires a business intelligence tool that will not only help their business grow, it will also grow with the company.Ī truly intelligent business intelligence (BI) platform brings the past and the present together to help create an informed visual roadmap for the future. Exponential data growth means companies of all sizes will need help managing and making sense of their data. Larger companies have more decision-makers, more data, and more datasets. Naturally, company leaders also use data to secure funding, plan new offerings, and make personnel decisions - and we've only hit the tip of the iceberg. The purchasing department checks inventory data before placing orders, and the logistics team tracks its shipments and deliveries. Sales departments use data to track sales and create goals. Marketing departments rely on data to monitor social media or email campaigns along with other marketing efforts. Data describes your customers, helps you attract and keep new customers, predicts trends, tracks inventory, and follows world events that could impact your company, etc.Įven the smallest companies wouldn't dare to make a big decision without consulting data. Aside from its employees, a company's data is its biggest asset.
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