Tag: Analytics

How ML and AI will transform business intelligence and analytics

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For 10 years the prevailing trend in business intelligence (BI) and analytics has been the move toward self service. That’s about to change. In 2018 and beyond, we’ll see a growing list of what many call “smart” capabilities powered by machine learning (ML) and artificial intelligence (AI). These features are sure to help us move beyond the limits of the self-service era.

As I explain in a my latest report, How Machine Learning & Artificial Intelligence Will Change BI & Analytics, we’re already starting to see smart capabilities in five areas: Data prep, discovery, analysis, prediction, and AI-powered prescriptive applications. My research details investments being made by more than 20 startups and 14 established BI and analytics vendors to advance the state of the art.

Expect a steady drumbeat of announcements throughout 2018 and beyond about ML applied to tasks including cleansing and combining data, discovering new

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Business Intelligence VS Data Analytics

To an outsider, Data Analytics and Business Intelligence might look similar and serving the same purpose, while they may not have the same outcomes. Here we are trying to explain the difference between the two to the best of our abilities.

Business Intelligence (BI) helps different organizations in better decision-making leveraging a wide range of latest tools and methods. It is the broadest category involving data analytics, data mining and big data. BI involves varied processes and procedures which help in data collection, sharing and reporting to ensure better decision making. With recent advancement in BI tools, users can generate reports and visualizations all by themselves, without relying on IT staff.

Extracting data for business Intelligence

According to CEO/Founder of Big Data-Startups, Mark van Rijmenam, “the difference between Business Intelligence and Data Analytics lies in the fact that Business Intelligence helps in making business decisions based on past results while data analytics helps

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Business Intelligence vs. Data Analytics; What’s the Difference?

Business Fight

There is a clear overlap that exists between business intelligence and data analytics, and this is evident by the fact that the two terms are used interchangeably. When asked, most industry experts will group the two terms together, but for those that are serious about turning data into actionable insights, it is important to differentiate them.

Download Link to Business Intelligence & Data Analytics Buyer's Guide

Even though the vast majority of enterprise organizations deploy one right next to the other, the two processes are different, and one thing is for sure – you can’t successfully practice one without the other. In an attempt to gain a clearer focus, let’s break each one down.

Business Intelligence

Business intelligence is the use of data to help make business decisions. BI as it’s commonly referred to, is a broad umbrella term for the use of data in a predictive environment. Business intelligence encompasses analytics, acting as the non-technical sister term used to

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Microsoft breaks through in the Gartner Magic Quadrant for Business Intelligence and Analytics Platforms

Today I’m thrilled to share that for the second year in a row, Microsoft has been positioned furthest to the right for completeness of vision within the Leaders quadrant of Gartner’s 2017 Magic Quadrant for Business Intelligence and Analytics Platforms – the 10th consecutive year Microsoft has been positioned as a leader.

Graph shows Microsoft positioned ahead of competitors in "completeness of vision"

We’re humbled by this recognition for the innovation we’ve delivered with Microsoft Power BI in the past year, including significant growth in both the vision axis and execution axis since the 2016 report. But, more importantly, we’re encouraged by the progress we’ve made as a community in executing against the ambitious goal set when Power BI was made generally available only a short time ago in July 2015: Provide BI to more people than ever before, across all roles and disciplines within organizations.

Power BI is the modern business intelligence solution you can bet on. We will continue

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Business intelligence, data warehousing and analytics editorial from DMReview



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Business Intelligence and Data Analytics

Overview

Organisations across the world are struggling to develop the know-how
to aggregate, analyse, and most importantly monetise the growing surge
of available data. Corporate and government entities point to a shortage
of individuals that have the combined business, analytics, IT, and
communications skills required to be leaders in this field. The School
of Information Systems and Management at Carnegie Mellon University’s
Heinz College is perfectly positioned to develop these leaders with our
world-renowned faculty teaching a cohesive blend of data analytics,
management, strategy, and IT courses.

Our Business Intelligence and Data Analytics (BIDA) programs are
aimed at developing an elite set of graduates cross-trained in business
process analysis, technology management and technically skilled in all
aspects of data science including predictive modelling, analytical
reporting, GIS mapping, segmentation analysis, and data visualisation.
Students will acquire the skills to integrate

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The history of business intelligence and analytics and what comes next

to our global readership, to avoid any possible local or regional bias, we should perhaps additionally consider fish and chips, borscht and potatoes, hummus and falafel, and likely many others, but I don’t want to belabor the point.

As best I could determine in my look back at the history of business intelligence, the term was first used by H. P. Luhn in an article entitled “A Business Intelligence System,” published in an IBM research journal in 1958. Luhn defined BI as “the ability to apprehend the interrelationships of presented facts in such a way as to guide action towards a desired goal.” Sounds straightforward.

During the next 30 years, we evolved the original concept through various stages of maturity: decision support systems (DSS) and executive information systems (EIS) were quite in vogue during the 1970s and 1980s. In 1989, a major milestone was achieved when Gartner Inc. analyst Howard … Read More

Data analytics and business intelligence: Understanding the differences

A popular saying among industry professionals — “data is the new oil” — implies that data, when harnessed (or, like oil, “refined”) properly, can provide high value. And they’re not very far off from the truth. In the last two decades, many organizations have added business intelligence features to their repertoire, concentrating their efforts on dashboarding, managed reporting, and data discovery. In the last few years, however, a new position has emerged — that of the data analyst. Spurred on by the success of data analytics-based businesses such as Uber and Amazon, plenty of regular businesses have tried to transform themselves into insight-driven organizations. But the journey has been far from easy, as is evident from organizations that are merely “dabbling” instead of “doing.” The thing is, despite sounding similar and serving many of the same purposes from an outsider perspective, data analytics and business intelligence deliver separate outcomes depending

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BARC Score | Enterprise Business Intelligence & Analytics Platforms 2019

This BARC Score focuses on Enterprise BI Platforms that are able to fulfill a broad set of BI requirements within the enterprise. BARC Score analyzes the strengths and weaknesses of the most important platform vendors in the BI market.

Overview

The market for business intelligence (BI) tools is highly competitive, with some large international incumbents, many successful vendors with a track record spanning decades, and countless smaller specialists with alternative and sometimes disruptive approaches to BI.

This report analyzes the strengths and challenges of the leading vendors that offer beneficial value to customers wanting to implement a ‘modern’ enterprise BI platform.

Characteristics of a modern enterprise BI platform

A modern enterprise BI and analytics platform is able to span traditional and explorative BI and analytics requirements both for standalone data and information applications but also when embedded in operational applications. With the increasing importance of data to not only support

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MSc. in Business Intelligence & Analytics

Projects in agile method

Students of the master programme in Business Intelligence & Analytics will execute projects to learn about the efficient (lean) and flexible (agile) way of working between Business and Information Systems.

The programme welcomes students coming from all over the world and of different study backgrounds and experiences assuring a diverse multicultural experience.

Lectures

Lectures are delivered by:

  • Practitioners, experts and managers from the business world who transfer their experiences in terms of knowledge and concrete examples to the students.
  • Faculty professors recognised as leaders in their fields of study.

Thanks to the programme, you will acquire general data awareness and skills, as well as a deep knowledge of business intelligence and analytics methodology and tools.

Dual-degree

Students can obtain a dual-degree

  • Master Business Informatiks (Data Science) from Aalen University in Germany by spending one semester in the partner university

What is it like

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