O'Reilly on Data

FEBRUARY 4, 2019

How companies in Europe are preparing for and adopting AI and ML technologies. In a recent survey , we explored how companies were adjusting to the growing importance of machine learning and analytics, while also preparing for the explosion in the number of data sources. In practice this means developing a coherent strategy for integrating artificial intelligence (AI), big data, and cloud components, and specifically investing in foundational technologies needed to sustain the sensible use of da

Machine Learning 277

Machine Learning Enterprise IoT Big Data 277

David Menninger's Analyst Perspectives

FEBRUARY 4, 2019

I am happy to share some insights gleaned from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Business Intelligence 207

Business Intelligence Analytics ROI Software 207

Srividya Sridharan

FEBRUARY 7, 2019

It’s early February. Punxsutawney Phil predicted an early spring this year, and there is hope (and warmth) in the air.[i] But it’s not always rosy for you as a data, analytics, and insights leader. You tirelessly toil to get value from your enterprise data and try to apply those insights at scale to impact business […].

Enterprise 88

Enterprise Data Analytics Analytics Predictive Analytics 88

IBM Big Data Hub

FEBRUARY 4, 2019

Join Dion Hinchcliffe as he stars in his first comic book, leading the charge to uncover the keys to a trusted, business-ready analytics foundation to know, trust, and use your data.

Digital Transformation 84

Digital Transformation Analytics 84

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.

Management

Business Over Broadway

FEBRUARY 4, 2019

A recent survey revealed that 69% of data pros have used at least one cloud computing product in the last 5 years while 62% of data pros have used at least one cloud computing service in the last 5 years. The most popular cloud computing products include AWS Elastic Compute, Google Cloud Engine and AWS Lambda. The most popular cloud computing services include Amazon Web Services, Google Cloud Platform and Microsoft Azure.

Data Science 76

Data Science Machine Learning Technology Analytics 76

David Menninger's Analyst Perspectives

FEBRUARY 6, 2019

I am happy to offer some insights on Information Builders drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Analytics 147

Analytics Business Intelligence ROI Software 147

IBM Big Data Hub

FEBRUARY 7, 2019

A faster journey to AI for the enterprise? What’s the secret? In this interview with Dinesh Nirmal, IBM vice president of analytics development, he shares the highlights of his upcoming Think session: “Modernizing Your Data Estates for an AI and Multicloud World.” On Wednesday, 13 February, he and David Bernert from The Boeing Company will discuss advancements in data that will give enterprises the edge.

Enterprise 78

Enterprise Analytics 78

MLWhiz

FEBRUARY 7, 2019

This is the second post of the NLP Text classification series. To give you a recap, recently I started up with an NLP text classification competition on Kaggle called Quora Question insincerity challenge. And I thought to share the knowledge via a series of blog posts on text classification. The first post talked about the various preprocessing techniques that work with Deep learning models and increasing embeddings coverage.

Deep Learning 73

Deep Learning Modeling 73

David Menninger's Analyst Perspectives

FEBRUARY 8, 2019

I am happy to offer some insights on MicroStrategy drawn from our latest Value Index research, which provides an analytic representation of our assessment of how well vendors’ offerings meet buyers’ requirements. The Ventana Research Value Index: Analytics and Business Intelligence 2019 is the distillation of a year of market and product research efforts by Ventana Research.

Analytics 138

Analytics Business Intelligence ROI Marketing 138

Jet Global

FEBRUARY 5, 2019

Are you making decisions based on bad data? It’s hard to answer that question because, truth be told, you don’t know you’re using bad data until it’s too late. . A? Gartner study ?states that about 40 percent of enterprise data is either inaccurate, incomplete, or unavailable. This poor data quality translates into an average of $15 million per year in a ripple effect of financial loss, missed opportunities, and high-risk decision making.

Data Quality 69

Data Quality Data Warehouse Business Intelligence Data Governance 69

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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?

Analytics

BizAcuity

FEBRUARY 8, 2019

A wise man once said nothing stays the same forever. We don’t know in which context he had said it, but it’s very true in today’s scenario, especially because of technology. Disruption is everywhere. Cloud computing first emerged in the 1950s with the development of microchips and mainframe computers. Users operated these computers through terminal computers for the efficient use of CPU resources.

Business Intelligence 69

Business Intelligence Data mining Data-driven Software 69

Dataiku

FEBRUARY 6, 2019

I recently moved to New York City, a true abundance of riches. I wanted to find “my coffee shop,” but sampling different locales is exhausting and disheartening. I cannot fathom trying a new cafe that could have watery coffee when I already know a spot that is perfectly fine. However, my current champion is two subways and a ten-minute walk from my apartment, so the utility value is low.

Machine Learning 64

Machine Learning 64

Cloudera

FEBRUARY 7, 2019

ATB Financial is Alberta’s largest home grown financial institution, and prides itself on its customer obsession, putting the over 750,000 Albertans at the centre of all that they do. As a result, ATB is constantly transforming in order to ensure it can continue to deliver unparalleled value to Albertans. A key pillar in the transformation journey is focused on robust data operations that can help ATB deliver timely, relevant and delightful service.

Big Data 63

Big Data Data Analytics Analytics Data Architecture 63

Timo Elliott

FEBRUARY 4, 2019

Over 50 tonnes of plastic waste were generated across the European Union last year, according to a study by the World Wildlife Fund , and consumers are increasingly concerned about the potential environmental impacts vividly illustrated in programs such as the BBC’s Blue Planet. Stephen Jamieson , Head of SAP Leonardo in the UK, saw an opportunity to innovate with purpose.

Machine Learning 55

Machine Learning Big Data Testing Technology 55

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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.

Visualization

Sanjeev Mohan

FEBRUARY 6, 2019

Is Google Cloud Platform Ready to Run Your Data Analytics Pipeline? This is the focus of my latest research which published in Jan 2019. So, why did I decide to write on this topic? I am glad you asked. My journey in helping our customers with their technical queries started when I joined Gartner in late 2016. At that time, the burning topic was choosing the right database for burgeoning use cases.

Data Analytics 49

Data Analytics Analytics Data Governance Experimentation 49

Dataiku

FEBRUARY 3, 2019

The Super Bowl has a lot of traditions: great ads , good comfort food , and if you’re unlucky, a free cab home. But there is an important question that is likely to impact your overall happiness and satisfaction this Sunday: what awesome brew should I buy to get us through the game?

Analytics 53

Analytics 53

Data Insight

FEBRUARY 7, 2019

“ Through data, the unexpected truth and authenticity of the world around us is revealed. ” — Carmen Vicelich, Data Insight CEO. The power of data: how to evolve and compete in the age of the customer We are now living in the age of the customer. Technology, social mobility and connectivity mean our customers no longer compare us to the company down the road – but to global brands that are well ahead of the game.

Data-driven 40

Data-driven Metrics Measurement Marketing 40

Timo Elliott

FEBRUARY 2, 2019

A keynote at the SOA People conference, on the theme of Building The Intelligent Enterprise. Slides: ? ?. Building the Intelligent Enterprise from Timo Elliott.

Enterprise 54

Enterprise Digital Transformation 54

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.

Experimentation

bridgei2i

FEBRUARY 8, 2019

THE CURRENT STATE OF AI IN SALES: Just like the story of AI, the story of sales too is a series of advancements. In a specific way, the current state of AI in sales is a convergence of advancements in various disciplines that hold tremendous potential to transform the world of sales. These are the same set of advancements that I covered in the previous section.

Sales 40

Sales B2B Cost-Benefit Structured Data 40

Smarten

FEBRUARY 7, 2019

As the need for advanced analytics increases in organizations, enterprises large and small struggle to find and sustain the professional resources they need to meet their requirements for data, analysis and strategic direction. In some businesses, Data Scientists, professional analysts and IT staff are often buried under requests for analysis and data and, as a result, these teams are unable to focus on strategic issues and on crucial questions that require 100% accuracy to drive the direction o

Optimization 40

Optimization Analytics Predictive Modeling Data-driven 40

Data Insight

FEBRUARY 7, 2019

Give any two data analysts the same sample and – in theory – they should derive the same insights. But true insight requires more than number crunching. It requires a little art. In a recent article, Data Insights’ CEO Carmen Vicelich says “The truth is there are many things you can do with data, but real, meaningful and actionable insight requires more than just a data sample and a fancy toolset.

Marketing 40

Marketing IT 40

Data Virtualization

FEBRUARY 6, 2019

Fresh from her success in supplying real-time transaction data to the call center using the Denodo Platform, Alice Well, recently appointed CIO of Advanced Banking Corporation (ABC), hears the three familiar, demanding raps on her office door. She glances toward. The post A Warehouse in a Lake, Data Virtually appeared first on Data Virtualization and Modern Data Management.

Management 40

Management Data Warehouse Data Lake Data Governance 40

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

Jen Stirrup

FEBRUARY 3, 2019

I’m writing this post for me, more than anyone else. I keep forgetting! Log into your Power BI tenant and click on the Question Mark at the top right hand side. Look for the option About Power BI. Here is an illustration below: . Choose the option About Power BI and you will get a window appear. It’s the last item that shows what you need: //embedr.flickr.com/assets/client-code.js.

IT 40

IT 40

Smarten

FEBRUARY 4, 2019

Data Literacy and Self-Serve Data Prep Encourage Citizen Data Scientists! In years past, data preparation was the domain of IT professionals and data scientists. In order to prepare data for analysis, one had to find, gather, and prepare the data and that preparation included cleaning, combining, reduction and shaping of the data. For the average manager, executive or business user, this complex process meant that they could not receive analysis or reports in a timely manner and that results wer

Machine Learning 40

Machine Learning Data Integration Reporting Management 40

Data Insight

FEBRUARY 7, 2019

By Carmen Vicelich, Data Insight CEO A round-up of thoughts and top trends from the NZ Marketing Association’s ‘Smarter Data 2017’ conference. When the top five companies in the world have all built their value on data – not products – there’s no doubting data is finally at the top table and being recognised as a key differentiator. This was further reinforced at the Marketing Association’s sell-out ‘Smarter Data’ event which I had the privilege of chairing on the 11th April 2017.

Machine Learning 40

Machine Learning Testing Marketing Measurement 40

Teradata

FEBRUARY 6, 2019

Kevin Lewis explains the role of chief of data officer.

56

56

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Start-ups & SMBs launching products quickly must bundle dashboards, reports, & self-service analytics into apps. Customers expect rapid value from your product (time-to-value), data security, and access to advanced capabilities. Traditional Business Intelligence (BI) tools can provide valuable data analysis capabilities, but they have a barrier to entry that can stop small and midsize businesses from capitalizing on them.

Analytics

Nutanix

FEBRUARY 5, 2019

Businesses have increasingly been adopting a multi-cloud approach for their IT infrastructure with applications and workloads running in both public and private cloud environments.

IT 20

IT 20

Domino Data Lab

FEBRUARY 4, 2019

In Paco Nathan ‘s latest column, he explores the role of curiosity in data science work as well as Rev 2 , an upcoming summit for data science leaders. Introduction. Welcome back to our monthly series about data science. This month, let’s explore two themes in detail: take an in-depth look at Rev 2 and exploring how curiosity plays a vital, and perhaps non-intuitive, role in data science work.

Data Science 66

Data Science Experimentation Data-driven Machine Learning 66

erwin

FEBRUARY 7, 2019

Organization’s cannot hope to make the most out of a data-driven strategy, without at least some degree of metadata-driven automation. The volume and variety of data has snowballed, and so has its velocity. As such, traditional – and mostly manual – processes associated with data management and data governance have broken down. They are time-consuming and prone to human error, making compliance, innovation and transformation initiatives more complicated, which is less than ideal in the informati

Metadata 96

Metadata Insurance Data-driven Cost-Benefit 96

Teradata

FEBRUARY 4, 2019

Teradata was recently named a leader in the Gartner Magic Quadrant for Data Management Solutions for Analytics.

IT 40

IT Management Analytics 40

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.

Manufacturing