June, 2018

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Six Nudges: Creating A Sense Of Urgency For Higher Conversion Rates!

Occam's Razor

By every indicator available, ecommerce is continuing to grow at an insane speed. Although it may seem impossible to imagine with ecommerce already totaling up to 5% of overall commerce, there’s astronomical growth still to come. Still, I’m heartbroken that some the simplest elements of ecommerce stink so much. It is 2018—why are there still light gray below-the-fold add to cart buttons?

Strategy 124
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Getting To Trusted Data Via AI, Machine Learning And Blockchain

Bruno Aziza

Establishing trust in data is critical. Organizations are now employing AI, Machine Learning, Blockchain to ensure data reliability and integrity.

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How Data Science Experience improves accuracy for the insurance industry

IBM Big Data Hub

In this Q&A, IBM financial services solution architect Irina Saburova discusses an insurance use case with IBM Data Science Marketing Lead Rosie Pongracz. In this scenario common to the insurance industry, an organization needs to adjust its operations based on upcoming weather event and multiple weather indicators can improve forecast accuracy.

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Use Text Analytics Technologies To Handle Mountains Of Unstructured Data

Boris Evelson

Enterprises are sitting on mountains of unstructured data – 61% have more than 100 Tb and 12% have more than 5 Pb! Luckily there are mature technologies out there that can help. First, enterprise information architects should consider general purpose text analytics platforms. These are capable of handling most if not all text analytics use […].

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How To Get Promoted In Product Management

Speaker: John Mansour

If you're looking to advance your career in product management, there are more options than just climbing the management ladder. Join our upcoming webinar to learn about highly rewarding career paths that don't involve management responsibilities. We'll cover both career tracks and provide tips on how to position yourself for success in the one that's right for you.

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The 5 best self-service BI tools compared

CIO Business Intelligence

Business intelligence (BI) and analytics platforms are a staple of informatics for medium to large businesses. Visual-based data discovery has been a key component of BI since about 2004; this trend has moved the responsibility for analytics from IT to self-service by business analysts and managers, with support from data scientists and database administrators.

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Cassandra vs. HBase: twins or just strangers with similar looks?

ScienceSoft

Similar at first glance, Cassandra and HBase actually are quite different in terms of architecture, performance and data models. What are these differences and how do they influence the tasks that HBase and Cassandra perform? It’s all here.

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The State Of Tech In 3 Graphs: Artificial Intelligence, The Cloud And Your Money

Bruno Aziza

Mary Meeker is a legend in Silicon Valley. Ever year, she comes out with what many think is the most complete and thorough analysis of the technology industry. Her presentations are full of great graphs, her slides full of data.there is one problem though.

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4 steps for running a machine learning pilot project

IBM Big Data Hub

Running a machine learning pilot project is a great early step on the road to full adoption. To get started, you’ll need to build a cross-functional team of business analysts, engineers, data scientists and key stakeholders. From there, the process looks a lot like the scientific method taught in school.

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The Importance of Planning and Forecasting in BI

Paris Technologies

The budgeting and forecasting process for most organizations is long and tedious and occurs on an annual basis, at least. Companies try to do it more often to improve accuracy and aim to ultimately implement a procedure for continuous planning or rolling forecasts. Unlike any other business process, budgeting and forecasting is unique because it is […].

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CEOs should stop saying this about tech

Mark Raskino

Here’s something that I sometimes hear CEOs and other business leaders say – and seemingly without much forethought. “Of course, the technology is the easy bit.” It’s one of those trite phrases that gets picked up and repeated in everyday corporate life, as if they were statements of obvious truth and wisdom, upon which we all agree.

IoT 49
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Navigating the Future: Generative AI, Application Analytics, and Data

Generative AI is upending the way product developers & end-users alike are interacting with data. Despite the potential of AI, many are left with questions about the future of product development: How will AI impact my business and contribute to its success? What can product managers and developers expect in the future with the widespread adoption of AI?

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Cassandra Performance: The Most Comprehensive Overview You’ll Ever See

ScienceSoft

Rumor has it: Apache Cassandra performance is amazing. But are there any grounds for these talks? Should you immediately fall in love with Cassandra because ‘she’ is so cool or should you just stay friends? Make the decision here.

IT 67
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2 Success Factors Every Top IRM Tech Solution Must Deliver

John Wheeler

Have you ever been driving your car down the road when you notice the ride is bumpier than usual? Or perhaps, the car strangely veers to the right or the left? These signs point to the fact that your wheels are not balanced and aligned properly. The same can occur for integrated risk management (IRM) technology customers. Top IRM technology solutions deliver two success factors – balance and alignment – to customers seeking to add value to the business.

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Understanding Blockchain 101: Untangling Myth from Reality

Bruno Aziza

Businesses are taking a serious look at Blockchain. But, how much is future potential versus current adoption. This post takes a look at the state of Blockchain in industry today.

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7 GDPR readiness success stories to inspire any company

IBM Big Data Hub

Businesses are likely to look back on the early days of the GDPR and tell stories about how their relationships with customers changed forever. What will your story be?

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Get Better Network Graphs & Save Analysts Time

Many organizations today are unlocking the power of their data by using graph databases to feed downstream analytics, enahance visualizations, and more. Yet, when different graph nodes represent the same entity, graphs get messy. Watch this essential video with Senzing CEO Jeff Jonas on how adding entity resolution to a graph database condenses network graphs to improve analytics and save your analysts time.

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Brittleness and incremental improvement

DMBS2

Every system — computer or otherwise — needs to deal with possibilities of damage or error. If it does this well, it may be regarded as “robust”, “mature(d), “strengthened”, or simply “improved” * Otherwise, it can reasonably be called “brittle” *It’s also common to use the word “harden(ed)” But I think that’s a poor choice, as brittle things are often also hard. 0.

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Martech spending in 2018: What CIOs need to know

CIO Business Intelligence

Forty-two percent of respondents to CIO' s recent State of the CIO survey say that their marketing department currently has budget specifically earmarked for investments in technology products and services — almost all of them within the next three years. If that figure sounds high to you, it shouldn't. As David Ginsburg, vice president of marketing at Cavirin, said when asked about that figure, "What is strange is that only 42 percent have explicitly budgeted for tech.

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Introducing Blended Learning From Cloudera University

Cloudera

Over the past decade, Cloudera University has taught more than 50,000 developers, administrators, analysts, and data scientists how to apply big data technologies. Developers are learning the APIs, so they can create new applications that were never before possible. Administrators learn to plan, install, monitor, and troubleshoot clusters. And analysts discover the power of SQL over large, diverse datasets.

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Successful CPM Projects: Choose a Partner, not a Vendor

Jedox

This is the third in a series of blogs discussing the requirements of a successful Corporate Performance Management (CPM) implementation. The first two blogs stressed the importance of Executive Involvement and explained why the Office of the CFO, not IT, should lead the implementation. This installment encourages the customer to seek a partner focused on CPM, not a vendor dedicated to selling software.

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Beyond the Basics of A/B Tests: Highly Innovative Experimentation Tactics You Need to Know

Speaker: Timothy Chan, PhD., Head of Data Science

Are you ready to move beyond the basics and take a deep dive into the cutting-edge techniques that are reshaping the landscape of experimentation? 🌐 From Sequential Testing to Multi-Armed Bandits, Switchback Experiments to Stratified Sampling, Timothy Chan, Data Science Lead, is here to unravel the mysteries of these powerful methodologies that are revolutionizing how we approach testing.

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Why You Need a Connector Strategy in the Digital Era

DataRobot Blog

by Jen Underwood. Both data-driven organizations and analytics software vendors today face a wide spectrum of complex challenges navigating an entirely new world of cloud app data sources. From security to agility, scale, Read More.

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Adding MongoDB to the IBM enterprise database ecosystem

IBM Big Data Hub

The modern data landscape demands more than one type of database. That’s IBM has rolled out JSON-document-based databases in Db2 and Cloudant, as well as partnered with select database providers to offer developer-focused database services through the IBM Compose platform.

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What is Hierarchical Clustering and How Can an Organization Use it to Analyze Data?

Smarten

This article discusses the analytical method of Hierarchical Clustering and how it can be used within an organization for analytical purposes. What is Hierarchical Clustering? Hierarchical Clustering is a process by which objects are classified into a number of groups so that they are as much dissimilar as possible from one group to another group and as much similar as possible within each group.

IT 40
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IBM CDO Conference: The Chief Data Officer Role Is Evolving

Hurwitz & Associates

By Jean S. Bozman. Chief Data Officers (CDOs) have a weighty responsibility: they are “on point” to find the actionable insights and data trends from analysis of data lakes, data repositories and virtual “seas” of data flowing across their large organizations. Data silos, different data formats – and organizational changes combining disparate data systems – make the CDO’s tasks challenging.

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Manufacturing Sustainability Surge: Your Guide to Data-Driven Energy Optimization & Decarbonization

Speaker: Kevin Kai Wong, President of Emergent Energy Solutions

In today's industrial landscape, the pursuit of sustainable energy optimization and decarbonization has become paramount. Manufacturing corporations across the U.S. are facing the urgent need to align with decarbonization goals while enhancing efficiency and productivity. Unfortunately, the lack of comprehensive energy data poses a significant challenge for manufacturing managers striving to meet their targets.

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9 ways to get more value from business intelligence in 2018

CIO Business Intelligence

For far too many organizations, business intelligence (BI) brings to mind simple statistical summaries in stodgy, dated reports. But beneath BI’s dull surface, keen insights await — especially for those willing to revamp their business intelligence strategy to tackle the kinds of issues forward-thinking organizations are already addressing with modern BI.

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Finally, we can talk about SAP HANA on Nutanix!

Nutanix

We’ve been struggling for months now to hold our tongues and not prematurely talk about this popular topic. We are at the cusp of yet another exciting and natural next step for the Nutanix Enterprise Cloud OS based on hyperconverged infrastructure (HCI), as we continue to expand into the core of the enterprise data center.

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Buyer Beware: The DOMO IPO

DataRobot Blog

by Jen Underwood. In light of recent S-1 confessions and warnings about DOMO’s precarious situation, my condolences go out to DOMO’s customers, staff and investors. If DOMO does not pull off a successful IPO, Read More.

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Why digital business needs a trusted data foundation

IBM Big Data Hub

This is an era in which everything has become digital. We live in the data-driven society. The difficulty is that all this digital technology still doesn’t totally cooperate.

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Peak Performance: Continuous Testing & Evaluation of LLM-Based Applications

Speaker: Aarushi Kansal, AI Leader & Author and Tony Karrer, Founder & CTO at Aggregage

Software leaders who are building applications based on Large Language Models (LLMs) often find it a challenge to achieve reliability. It’s no surprise given the non-deterministic nature of LLMs. To effectively create reliable LLM-based (often with RAG) applications, extensive testing and evaluation processes are crucial. This often ends up involving meticulous adjustments to prompts.

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What is Karl Pearson Correlation Analysis and How Can it be Used for Enterprise Analysis Needs?

Smarten

This article explains the Karl Pearson Correlation method of analysis, and how it can be applied in business. What is the Karl Pearson Correlation Analytical Technique? Correlation is a statistical measure that indicates the extent to which two variables fluctuate together. A positive correlation indicates the extent to which those variables increase or decrease in parallel.

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What AI Means to a Retailer Dedicated to Customer Experience

Birst BI

Retailers are focused more than ever on quickly adjusting to changing customer preferences and demand. Specialty’s Café and Bakery is a great example of a retailer that is using data to drive decisions related to product development and selection, inventories, staffing, and more to attract and keep customers. For example, retailers rely on business intelligence (BI) tools to predict future demand for products around known factors such as special events or holidays.

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IDG Contributor Network: The eye-opening new world of alternative investor data

CIO Business Intelligence

Investors, whether they be day traders at home or managers of large hedge funds, are data hungry. They pore over earnings reports and company filings and jump to read news alerts. If they’re on the super-sophisticated side, they may be using data models. And if they’re on the cutting edge, they may be using new “alternative” data sets to inform their decisions.

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Turning petabytes of pharmaceutical data into actionable insights

Cloudera

Authors: Mai N. Nguyen, Accenture & Mitch Gomulinski, Cloudera. Imagine storing the DNA of the entire population of the US – and then cloning them, twice. That’s the equivalent of 1 petabyte ( ComputerWeekly ) – the amount of unstructured data available within our large pharmaceutical client’s business. Then imagine the insights that are locked in that massive amount of data.

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Understanding User Needs and Satisfying Them

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.