2017

A Business Analyst's Guide To Managing Change Requests

BA Learnings

It’s common knowledge that people tend to resist change as much as they can. However, without change, there can’t be progress and BAs would certainly not have that much to do. When working on large projects, change requests from stakeholders are to be expected. Successful project managers and analysts know how to manage them without bringing the project to a standstill.

Artificial Intelligence: Implications On Marketing, Analytics, And You

Occam's Razor

A rare post today. It looks a little further out into the future than I normally tend to. It attempts to simplify a topic that has more than it’s share of coolness, confusion and complexity. While the phrase Artificial Intelligence has been around since the first human wondered if she could go further if she had access to entities with inorganic intelligence, it truly jumped the shark in 2016.

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Virtually Celebrate New Year’s Eve in Every Timezone with the ‘VRChat’ Community

IBM Big Data Hub

Ever wished you could jet set around the world fast enough to ring in the New Year at a party in every timezone? Well that might not be quite possible, but VRChat is offering something close. VRChat , a social VR experience supporting major PC VR headsets via Steam , is celebrating New Year’s Eve virtually in every timezone, every hour, on the hour. Fireworks included. Image courtesy VRChat.

Predictions 2018: The Blockchain Revolution Will Have To Wait A Little Longer

Martha Bennett

The visionaries will forge ahead, those hoping for immediate industry and process transformation will give up. This is the answer I usually give when asked for a one-sentence summary of how I see 2018 shaping up in the blockchain technology arena. Following blockchain technology feels a little like living in two parallel universes: One is […]. blockchain prediction

Monetizing Analytics Features: Why Data Visualization Will Never Be Enough

Five years ago, data visualizations were a powerful way to differentiate a software application. Today, free visualizations seem to be everywhere. Two trends are forcing application providers to rethink how they offer analytics in their products.

Predictions 2018: AI Hard Fact – Treat It Like A Plug-And-Play Panacea and Fail

Boris Evelson

Look right, look left, you’ll see a fellow CIO contemplating their AI move. Failing to act is not an option in most organizations. However, as enterprises are kicking off their AI pilots or seeing early results, the honeymoon is over as enterprises that naively celebrated the cure-all promises of artificial intelligence (AI) technologies is over. Enterprises needed better data foundations. They underestimated the level of business expertise […].

Our quest for robust time series forecasting at scale

The Unofficial Google Data Science Blog

by ERIC TASSONE, FARZAN ROHANI We were part of a team of data scientists in Search Infrastructure at Google that took on the task of developing robust and automatic large-scale time series forecasting for our organization. In this post, we recount how we approached the task, describing initial stakeholder needs, the business and engineering contexts in which the challenge arose, and theoretical and pragmatic choices we made to implement our solution.

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Just Buying Into Modern BI and Analytics? Get Ready for Augmented Analytics, the Next Wave of Market Disruption

Rita Sallam

Machine learning automation is affecting all of enterprise software, but will completely transform how we build, analyze, and consume data and analytics. Over the past 10 years or more, visual-based data discovery tools (e.g. Tableau, Qlik, Tibco Spotfire) have disrupted the traditional BI market (e.g. IBM Cognos, SAP BusinessObjects). Yet, as transformative as these tools have been, analytics is once again at a critical inflection point.

Smart Data Visualization Walks You Through to Success

Smarten

Take the Guesswork Out of Analytics with Smart Data Visualization! Smart data visualization takes the guesswork out of data analysis. Why ask your business users to use cumbersome, difficult tools to analyze data or expect them to wait for professional analysts or IT staff to satisfy their analytical needs. They have a job to do and you hold them accountable for results but if they don’t have the right data visualization tools, they can’t get the most out of data.

Whose cloud? The business strategy question every CEO should consider.

Mark Raskino

Before we get into this important issue I have to declare a disinterest. I’m not a cloud analyst at Gartner. I don’t cover the vendors or their offerings. I can’t tell you which one is best under different circumstances. I have many colleagues who can help you with those decisions. What I do know is this – deciding which cloud(s) your company will become reliant on is a strategy question that cannot be left to technical thinkers alone.

Big Data: Examples, Sources and Technologies explained

ScienceSoft

While defining big data, we share multi-industry examples of its practical application, list its internal and external sources, as well as name most popular big data technologies

The 2023 Supply Chain Crystal Ball: Challenges and Solutions

Speaker: Olivia Montgomery, Associate Principal Supply Chain Analyst

Curious to know how your peers are navigating ongoing disruption? In this webinar, you’ll gain actionable insights from Olivia Montgomery as she walks us through Capterra’s extensive research on how businesses - notably small and midsize businesses - are addressing supply chain challenges in 2023.

A List of Business Process Management Certifications

BA Learnings

While there’s nothing like having some experience under your belt, Business Process Management (BPM) certifications can aid analysts in some key ways: they serve as concrete evidence of business process management knowledge; offer the opportunity to learn new concepts /best practices; and benefit from the experience of trainers/mentors. While some of these certifications are offered by professional organizations, others have been put together by software vendors.

It's Not The Ink, It's The Think: 6 Effective Data Visualization Strategies

Occam's Razor

Ten years, and the 944,357 words, are proof that I love purposeful data, collecting it, pouring smart strategies into analyzing it, and using the insights identified to transform organizations. In the quest for that last important bit, I am insanely obsessive about 1. simplification and 2. pressing the right emotional buttons.

Learning Machine Learning? Six articles you don’t want to miss

IBM Big Data Hub

Digital disruption has revolutionized the way we live and do business — and machine learning is the latest wave of that revolution

Big Data Storage and Graph-Based Analytics for Cancer Research

DSI Analytics

Big data technologies are playing an increasing role in cancer research. Two ways that I’ll touch on are the storage of an exponentially growing quantity of sequenced genomic data and analysis of pathway disruption by large-scale graph algorithms. There is an amazing diversity in cancer cells. A single tumor may contain 100 billion cells, each […]. The post Big Data Storage and Graph-Based Analytics for Cancer Research appeared first on DSI Analytics

5 Powerful Prescriptive Analytics Examples in Supply Chain

Prescriptive analytics is a type of advanced analytics that optimizes decision-making by providing a recommended action. Supply chain, with its complex planning questions, is typically an area where optimization technology is required. Read about 5 use cases.

Everything you wanted to know about SAP Leonardo but were afraid to ask

Boris Evelson

Large enterprise software vendors seem to be enamoured with using the names of historical figures or literary characters as brand names. Unfortunately, this is really confusing for the buyers, since the vendors apply these branding names differently. For example (in an increasing order of branding approach complexity): OpenText Magellan is a collection of business intelligence […].

Causality in machine learning

The Unofficial Google Data Science Blog

By OMKAR MURALIDHARAN, NIALL CARDIN, TODD PHILLIPS, AMIR NAJMI Given recent advances and interest in machine learning, those of us with traditional statistical training have had occasion to ponder the similarities and differences between the fields. Many of the distinctions are due to culture and tooling, but there are also differences in thinking which run deeper. Take, for instance, how each field views the provenance of the training data when building predictive models.

Advice for aspiring data scientists and other FAQs

Data Science and Beyond

Aspiring data scientists and other visitors to this site often repeat the same questions. This post is the definitive collection of my answers to such questions (which may evolve over time). How do I become a data scientist? It depends on your situation. Before we get into it, have you thought about why you want to become a data scientist? Hmm… Not really. Why should I become a data scientist? I can’t answer this for you, but it’s great to see you asking why.

Hyperopt - A bayesian Parameter Tuning Framework

MLWhiz

Recently I was working on a in-class competition from the “How to win a data science competition” Coursera course. You can start for free with the 7-day Free Trial. Learned a lot of new things from that about using XGBoost for time series prediction tasks. The one thing that I tried out in this competition was the Hyperopt package - A bayesian Parameter Tuning Framework. And I was literally amazed

Intent Signal Data 101

Intent signal data helps B2B marketers engage with buyers sooner in the sales cycle. But there are many confusing terms used to describe intent data. Read this infographic to better understand three common areas of confusion.

Smart Data Visualization: Simpler, Better, Clearer, Faster

Smarten

Smart Visualization Tools: Analysis and Data Displays Made Simple (and Clear). Smart Data Visualization! This concept seems alien to some people. Is it data that can read your mind and automatically display itself in a way that will help you understand? Is it a method you use to see data in a clear way; a technique you learn in a class? The answer is yes…and no.

A story chart of the corporate information age

Mark Raskino

It was nineteen-eighty-something. “ Information technology, is a societal, epochal technology ” said my university lecturer, quoting a translated Japanese author (that made the insight seem even more wise and visionary). Like … wow man.

4 Types of Data Analytics to Improve Decision-Making

ScienceSoft

Learn about different types of data analytics and find out which one suits your business needs best: descriptive, diagnostic, predictive or prescriptive

Business Analysts & The Anchor Effect

BA Learnings

I’ve always been intrigued by the concept of cognitive bias for the simple reason that it exposes the flaws in one’s thinking and ability to make sound decisions. Every analyst, and in fact everyone, stands to benefit from understanding what cognitive biases are so they can be kept to a minimum or spotted when interacting with others.

Modern Data Architecture for Embedded Analytics

Data has gone from a mere result of applications & processes to being crowned king. Picking the right avenue to data architecture depends on your organization’s needs. Development teams should build in stages, starting with a task that can be solved.

The Very Best Digital Metrics For 15 Different Companies!

Occam's Razor

The very best analysts distill, rather than dilute. The very best analysts focus, when most will tend to gather. The very best analysts are display critical thinking, rather than giving into what’s asked. The very best analysts are comfortable operating with ambiguity and incompleteness, while all others chase perfection in implementation / processing / reports.

Influencers assess 2017 and make predictions for 2018

IBM Big Data Hub

As the year winds down, questions tend to arise about what the big trends of the past year have been and what the year to come may hold

Open Source: A primer for Big Data

DSI Analytics

It is nearly impossible to talk about Big Data without making frequent reference to a broad ecosystem of computer code that has been made available for use and modification by the general public at no charge. History of open source In the early days of computing, computer code could be considered an idea or method, […]. The post Open Source: A primer for Big Data appeared first on DSI Analytics. Technology apache hadoop Big Data open source

The Five Faces of the Analytics Dream Team

Darkhorse

The chasm between Business and IT is well documented and has existed since the first punch-card mainframe dimmed the lights of MIT to solve the ballistic trajectory of WWII munitions. Analytics and now Data Science are trapped in the middle. Everyone hopes they'll deliver the productivity gains, but the jury is still out. Some studies suggest that analytics projects have an 80% failure rate. A recent HBR article put it at 100% for data science projects. That’s abysmal.

A Deep Dive Into Supply Chain Strategy: Why Yours Isn't Working

Speaker: Michelle Meyer, Founder and CEO of MatterProviders

Michelle Meyer is here to walk you through the future of supply chain strategy, and why your current approach is probably not working. In this exclusive webinar, she will explore ways to develop and perfect your new supply chain design in this post-pandemic era of economic uncertainty.

Attributing a deep network’s prediction to its input features

The Unofficial Google Data Science Blog

By MUKUND SUNDARARAJAN, ANKUR TALY, QIQI YAN Editor's note: Causal inference is central to answering questions in science, engineering and business and hence the topic has received particular attention on this blog. Typically, causal inference in data science is framed in probabilistic terms, where there is statistical uncertainty in the outcomes as well as model uncertainty about the true causal mechanism connecting inputs and outputs.

Exploring and visualising reef life survey data

Data Science and Beyond

Last year, I wrote about the Reef Life Survey (RLS) project and my experience with offline data collection on the Great Barrier Reef. I found that using auto-generated flashcards with an increasing level of difficulty is a good way to memorise marine species. Since publishing that post, I have improved the flashcards and built a tool for exploring the aggregate survey data. Both tools are now publicly available on the RLS website.

How Women Are Shaping The Big Data Revolution

Bruno Aziza

Increasingly, women executives are being called upon to take the lead in shaping the critical business functions that are most necessary to ensuring business value from Big Data and analytics investments

White Paper: Self-Serve Data Preparation Provides Significant Benefit to the Enterprise

Smarten

By providing sophisticated analytical features and algorithms in an easy-to-use self-serve environment, the enterprise enables business users to perform data preparation and test theories and hypotheses and prototype on their own.

Getting Started With Scenario Modeling in Supply Chain Network Design

To build your supply chain’s agility and responsiveness, you need to look at scenarios more frequently instead of relying on a single plan. Let’s explore how you can apply scenario modeling in supply chain network design.