Sat.Dec 02, 2017 - Fri.Dec 08, 2017

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What BAs Should Know About Feedback Analysis

BA Learnings

Most people think they know what they’re good at. They are usually wrong. More often, people know what they’re not good at — and even then more people are wrong than right — Peter F. Drucker Peter Drucker emphasized the need for professionals to know themselves in order to manage themselves through feedback analysis. To perform effectively, people need to know and understand themselves.

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Top 10 IBM Big Data & Analytics Hub blog posts of 2017

IBM Big Data Hub

Readers of the IBM Big Data & Analytics Hub were hungry for knowledge this year. They voraciously read blog posts about incorporating machine learning, choosing the best possible data model, determining how to make the most of data science skills, working with open source frameworks and more. Here are our top 10 blog posts of 2017.

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New Book: Big Data, Big Dupe

Perceptual Edge

I’ve written a new book, titled Big Data, Big Dupe , which will be published on February 1, 2018. As the title suggests, it is an exposé on Big Data—one that is long overdue. To give you an idea of the content, here’s the text that will appear on the book’s back cover: Big Data, Big Dupe is a little book about a big bunch of nonsense. The story of David and Goliath inspires us to hope that something little, when armed with truth, can topple something big that is a lie.

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Assisted Predictive Modeling Guide Users Through the Maze

Smarten

What is Assisted Predictive Modeling? Anything that can help your business users to understand, interpret and analyze data is a help! Users have many tasks to perform in a given day and while analysis may not be their forte, they definitely need clear, concise data to share, to make decisions and to see opportunities, challenges and patterns. To be a positive asset to the business, your business users must be able to accurately plan and forecast everything from budgetary needs to team members an

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15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?

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I See What You Did There: Integrating Machine Intelligence And Human Intuition

Bruno Aziza

Technological advances come along so fast now, especially in the digital space, that some mistrust is expected. We especially don’t trust machine intelligence in part because we don’t understand it.

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Building a Self-Managed Shared Data Experience

Cloudera

Cloud promises many advantages as an environment for machine learning and analytics. Cloud makes it fast and easy to spin up resources for new applications. Cloud offers elasticity of those resources to efficiently support transient analytics workloads and data pipelines. Cloud offers self-service without waiting for IT infrastructure and operations teams.

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What is Self-Serve Data Preparation and How Can It Support Business Users?

Smarten

Self-Serve Data Preparation is the next generation of business analytics and business intelligence. Self-serve data preparation makes advanced data discovery accessible to team members and business users no matter their skills or technical knowledge. What is Self-Serve Data Preparation? In the past, preparing data for analysis was a time-consuming process, a task that was relegated to the IT team and involved complex tasks like Data Extraction, Transformation and Loading (ETL), access to data wa

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