Birst’s Connected Data Prep empowers business people to access and prepare data with a user-friendly, visual experience that eliminates the need for complicated scripting. Not only that, with Connected Data Prep you can network your analytics with data from colleagues, other departments, or your IT organisation, enriching your insights for smarter, more trusted decisions.
The data lake concept centers on landing all analysable data sets of any kind in raw or only lightly processed form into the easily expandable scale-out Hadoop infrastructure to ensure that the fidelity of the data is preserved.
Since its inception, the primary objective of business intelligence has been the creation of a top-down single source of truth from which organisations would centrally track KPIs and performance metrics with static reports and dashboards. This stemmed from the proliferation of data in spreadsheets and reporting silos throughout organisations, often yielding different and conflicting results. With this new mandate, BI-focused teams were formed, often in IT departments, and they began to approach the problem in the same manner as traditional IT projects, where the business makes a request of IT, IT logs a ticket, then fulfils the request following a waterfall methodology.
Imagine a cloud Business Intelligence system that can aggregate and analyse data from 400 data sources in a single view, go live in fewer than 90 days, and help achieve a five-fold increase in inventory turns. Let’s have a look at the Citrix case study, focusing on how Citrix has solved its data analytics problem and architected its digital supply chain with Birst.
Cloud-based Business Intelligence (BI) is the future. And one of the first BI vendors to capitalize on this trend is Birst - "the only enterprise BI platform in the cloud." This article will provide you with a case study of how Build.com drives their business forward with Birst’s cloud BI system.
Infor is a leading provider of business application software with more than 73,000 customers, recognised for providing specific functionality to the hospitality industry, speeding up deployment through built-in reports, graphs and key performance indicators (KPIs). At HITEC 2015, this business application giant announced the great effort and plans for its hospitality division.
In particular, Infor d/EPM for Hospitality is designed with the advanced functionality to help implement and facilitate analysis. Another great feature is Office Plus which integrates directly with Microsoft Excel.
That’s the reason why there is no surprise that some of Infor d/EPM for Hospitality's famous clients include Wyndham Hotel Group, Kempinski Hotels, Auberge Resorts, Intrawest Resorts and Hard Rock International.
Topics: Business Intelligence
The world of technologies recently is buzzing with a new terminology: “networked analytics”, which was marketed as the technology behind cloud-based Business Intelligence solution from Birst (recently acquired by Infor). Such breakthrough is expected to help businesses to manipulate data much better than what we are currently doing.
Earlier this year, Gartner published their 2018 Magic Quadrant for Analytics and Business Intelligence Platforms mentioning the trend of upgrading traditional solutions as well as expanding portfolios with new vendors as the market innovates on ease of use and augmented analytics.
CheapCaribbean used to heavily rely on Excel for data analysis, which was very time-consuming and not effective at realising the value of their data. In order to become a truly data-driven organisation, CheapCaribbean has adopted Birst, a leading cloud Business Intelligence solution provider. Its breadth of functionalities meets all of the company’s analytics needs while the modern networked analytics architecture is a perfect match with CheapCaribbean’s vision of taking the business to the next level. See what Jason Seiple, the Director of Data Analytics at CheapCaribbean, has to say about Birst in the following video.
Topics: Business Intelligence
Machine Learning – a branch of AI, is changing the way companies utilise their Big Data reserve, which allowed them to reshape customers’ behaviour. Machine Learning based on the idea that machine can learn from data and recognise the patterns, which result in decisions and predictions with a degree of certainty.