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Interview with: Sankar Narayanan, Chief Practice Officer at Fractal Analytics

Corinium

How can advanced analytics be used to improve the accuracy of forecasting? The use of newer techniques, especially Machine Learning and Deep Learning, including RNNs and LSTMs, have high applicability in time series forecasting. Newer methods can work with large amounts of data and are able to unearth latent interactions.

Insurance 250
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What is the Future of Business Intelligence in the Coming Year?

Smart Data Collective

Prescriptive Analytics. In the future of business intelligence, it will also be more common to break data-based forecasts into actionable steps to achieve the best strategy of business development. Unique feature: custom visualizations to fit your business needs better. Natural Language Processing (NLP). 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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Your Data, Your Brand: Creating Trust in Integrated Workflows and Reporting

Sisense

These APIs empower developers to tap into any Sisense interface or functionality and enhance, rebrand, or integrate it into the brand’s own analytic apps and off-the-shelf business systems. Custom analytics with the Linux Pivot API. The joint project took only a few weeks and some well-planned lines of code.

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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. Thank you, Suvodip.

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Data virtualization unifies data for seamless AI and analytics

IBM Big Data Hub

Data virtualization empowers businesses to unlock the hidden potential of their data, delivering real-time AI insights for cutting-edge applications like predictive maintenance, fraud detection and demand forecasting. Despite heavy investments in databases and technology, many companies struggle to extract further value from their data.

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Create an end-to-end data strategy for Customer 360 on AWS

AWS Big Data

Customer 360 (C360) provides a complete and unified view of a customer’s interactions and behavior across all touchpoints and channels. This view is used to identify patterns and trends in customer behavior, which can inform data-driven decisions to improve business outcomes.