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What is the Future of Business Intelligence in the Coming Year?

Smart Data Collective

In the future of business intelligence, eliminating waste will be easier thanks to better statistics, timely reporting on defects and improved forecasts. Unique feature: custom visualizations to fit your business needs better. Today, finding what elements of your business are pulling you back is a hard task. SAP Lumira.

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5 Sources of Data for Customer Analytics and Their Benefits

Smart Data Collective

Therefore, you need sophisticated customer analytics to analyze complex customer behavior. This article will go over the concept of customer service analytics and some of the uses and advantages it could provide to a business. A high level of customer effort results in a poor customer experience.

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Different Tools for Different Tasks

Perceptual Edge

Presentation preparation (Preparing displays of data that will be presented in meetings or in custom reports). Customized analytical application development (Developing applications that others will use to analyze data in the same specific ways again and again).

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An In-Depth View of Data Science

Domino Data Lab

Data science is a field at the convergence of statistics, computer science and business. Data science is an interdisciplinary field within STEM that combines math and statistics, computer science, and business acumen to find patterns in complex datasets that can be used to improve decision making. What are Data Scientists?

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PODCAST: COVID19 | Redefining Digital Enterprises – Episode 9: The Impact of COVID-19 on Consumer Technology & Durables

bridgei2i

He brings deep experience supporting high tech e-commerce and retail clients in the areas of marketing, pre-sales analytics, and web analytics. Prior to that, he led digital and customer analytics engagements at Dell, HP, and GE. Hence, there is a rise of digitally engaging with customers.

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How Data Integration and Machine Learning Improve Retention Marketing

Business Over Broadway

Figure 1 includes a good illustration of different data sets and how they fall along these two size-related dimensions (For the interested reader, check out the figure in an interactive graphic ). In these situations, analytic results of a small set of accounts may be difficult to generalize to the entire customer base.

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Delivering Low-latency Analytics Products for Business Success

Rocket-Powered Data Science

I recently saw an informal online survey that asked users what types of data (tabular; text; images; or “other”) are being used in their organization’s analytics applications. This was not a scientific or statistically robust survey, so the results are not necessarily reliable, but they are interesting and provocative.

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