BA Learnings

DECEMBER 3, 2017

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.

Business Analysis 162

Business Analysis Management IT 162

IBM Big Data Hub

DECEMBER 4, 2017

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.

Big Data 81

Big Data Data Analytics Analytics Machine Learning 81

Perceptual Edge

DECEMBER 6, 2017

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.

Big Data 74

Big Data Visualization Publishing Marketing 74

Smarten

DECEMBER 4, 2017

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

Predictive Modeling 61

Predictive Modeling Modeling Predictive Analytics Forecasting 61

Speaker: Scott Sehlhorst

We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.

Management

Bruno Aziza

DECEMBER 8, 2017

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.

Technology 40

Technology IT 40

Cloudera

DECEMBER 7, 2017

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.

Management 40

Management Cost-Benefit Machine Learning Metadata 40

Smarten

DECEMBER 7, 2017

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

IT 40

IT Testing ROI Data Warehouse 40