DataKitchen

AUGUST 3, 2021

The data mesh design pattern breaks giant, monolithic enterprise data architectures into subsystems or domains, each managed by a dedicated team. With an architecture comprised of numerous domains, enterprises need to manage order-of-operations issues, inter-domain communication, and shared services like environment creation and meta-orchestration. A DataOps superstructure provides the foundation to address the many challenges inherent in operating a group of interdependent domains.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

Analytics Vidhya

AUGUST 5, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In neural networks we have lots of hyperparameters, it is. The post Hyperparameter Tuning Of Neural Networks using Keras Tuner appeared first on Analytics Vidhya.

Data Science 400

Data Science Publishing Analytics IT 400

Domino Data Lab

AUGUST 6, 2021

In the world of machine learning (ML) and artificial intelligence (AI), governance is a lifelong pursuit. All models require testing and auditing throughout their deployment and, because models are continually learning, there is always an element of risk that they will drift from their original standards. As such, model governance needs to be applied to each model for as long as it’s being used.

Machine Learning 145

Machine Learning Modeling Testing Risk 145

TDAN

AUGUST 3, 2021

Increasingly, external data (alternative data, public data, open data – call it what you want) is being called the “secret sauce” of driving advanced analytics, developing machine learning and AI capabilities, enriching existing models, and delivering unrealized insights to every part of your organization. The difficulty in connecting to this data is top of mind for […].

Machine Learning 145

Machine Learning Modeling Analytics IT 145

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

DataKitchen

AUGUST 3, 2021

The post Building a Modern Data Architecture for the 2020s first appeared on DataKitchen.

Data Architecture 147

Data Architecture 147

Analytics Vidhya

AUGUST 5, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction Data- a world-changing gamer is a key component for all. The post Let’s Understand All About Data Wrangling! appeared first on Analytics Vidhya.

Data Science 400

Data Science Publishing Analytics 400

TDAN

AUGUST 3, 2021

Through big data modeling, data-driven organizations can better understand and manage the complexities of big data, improve business intelligence (BI), and enable organizations to benefit from actionable insight. Big data modeling is an extension of data modeling, a practice adopted by many areas of Information Technology (IT), used to better understand enterprise data resources.

Business Intelligence 143

Business Intelligence Big Data Modeling Data-driven 143

Dataiku

AUGUST 4, 2021

“AI is starting to deliver on its potential” — it feels like years that people have been singing variations of this refrain, doesn’t it? And while organizations have come a long way with AI, I don’t think we’ve even scratched the surface when it comes to business potential with and value from AI. That’s why today, we’re proud to announce a $400 million Series E funding round that will allow Dataiku to unleash Everyday AI within exponentially more organizations around the world.

IT 122

IT 122

Analytics Vidhya

AUGUST 1, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Data Visualization Data Visualization techniques involve the generation of graphical or. The post Effective Data Visualization Techniques in Data Science Using Python appeared first on Analytics Vidhya.

Visualization 400

Visualization Data Science Publishing Analytics 400

Sisense

AUGUST 4, 2021

Blog. COVID-19 is a huge data story in many ways, and food delivery analytics are a big part of that. Online food ordering in 2020 hit $115 billion globally and could reach nearly $127 billion in 2021 according to an April 2021 report. For much of the pandemic, and through to today, diners switched from sit-down dining to takeout and delivery, a decision based as much on consumer access to data (like local infection rates) as local mandates that saw many restaurants unable to seat large numbers

Analytics 119

Analytics Optimization Marketing Sales 119

Speaker: David Bard, Principal at VP Product Coaching

In the fast-paced world of digital innovation, success is often accompanied by a multitude of challenges - like the pitfalls lurking at every turn, threatening to derail the most promising projects. But fret not, this webinar is your key to effective product development! Join us for an enlightening session to empower you to lead your team to greater heights.

Management

TDAN

AUGUST 3, 2021

Rigidly adhering to a standard, any standard, without being reasonable and using your ability to think through changing situations and circumstances is itself a bad standard. I guess I should quickly define what I mean by a “database standard” for those who are not aware. Database standards are common practices and procedures that are documented and […].

Data Quality 116

Data Quality Data Architecture Modeling Management 116

Smart Data Collective

AUGUST 1, 2021

Machine learning technology has profoundly impacted the IT sector. A growing number of IT professionals are using new tools that rely on advanced machine learning algorithms to complete some of the tasks they are charged with. One task that has been revamped with machine learning technology is data recovery. You can use machine learning to identify the files that were accidentally deleted much more easily and make sure they are adequately restored.

Machine Learning 115

Machine Learning Software Technology Risk 115

Analytics Vidhya

AUGUST 1, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Source Introduction: In this article, we will learn all the important. The post A Guide To Complete Statistics For Data Science Beginners! appeared first on Analytics Vidhya.

Statistics 389

Statistics Data Science Publishing Analytics 389

Cloudera

AUGUST 3, 2021

Minimizing Supply Chain Disruptions . January 2020 is a distant memory, but for most, the early days of the pandemic was a time that will be ingrained in memories for decades, if not generations. Over the last 18 months, supply chain issues have dominated our nightly news, social feeds and family conversations at the dinner table. Some but not all have stemmed from the pandemic. .

Analytics 108

Analytics Digital Transformation Risk Forecasting 108

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.

Testing

bridgei2i

AUGUST 5, 2021

Why Contextual Customer Data is Indispensable to Driving Superior Experiences. Paromita Mitra, Director -Digital Consulting, CX, BRIDGEi2i | Thomas Wieberneit, CRM & CX Evangelist, & Co-Founder, aheadCRM. Highlights. In this podcast, Thomas Wieberneit shares some fascinating insights into how companies can only be successful if their customers are successful. [03.28] What do organizations struggle with the most when it comes to providing superior experiences for their customers?

Enterprise 98

Enterprise Slice and Dice Consulting Digital Transformation 98

DataRobot

AUGUST 5, 2021

There’s a saying, “If you can’t say something nice, don’t say anything at all.” Is there too much hype about AI or too much doomsaying? AI Hype. In 2019, Utah struck a deal with Banjo, a threat detection firm selling AI services to process live traffic feeds, dispatch logs, and other data. Banjo claimed to use software that automatically detected anomalies to help law enforcement solve crimes and respond faster.

Uncertainty 98

Uncertainty Sales Risk Statistics 98

Analytics Vidhya

AUGUST 3, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In this article, you’ll learn about Python Data Types and. The post Data Types in Python You Need to know at the Beginning of your Data Science Journey appeared first on Analytics Vidhya.

Data Science 390

Data Science Publishing Analytics 390

Cloudera

AUGUST 6, 2021

Today’s organizations face rising customer expectations in a fragmented marketplace amidst stiff competition. This landscape is one that presents opportunities for a modern data-driven organization to thrive. At the nucleus of such an organization is the practice of accelerating time to insights, using data to make better business decisions at all levels and roles.

Data-driven 104

Data-driven B2B Data Strategy Strategy 104

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IT

FineReport

AUGUST 4, 2021

Emerging technologies are changing the way companies collect and extract available insights from data. More and more companies use data to drive their decisions. This makes cutting-edge analysis and business intelligence strategies one of the best advantages companies can have. The more you know about business intelligence trends, the more accurate decision-making you will make.

Business Intelligence 98

Business Intelligence Data-driven Dashboards Internet of Things 98

Boris Evelson

AUGUST 4, 2021

Multiple BI platforms in an enterprise are here to stay. Respondents to an informal social media survey that I’ve been running for the last couple of years report that 25% organizations use 10 or more business intelligence (BI) platforms, 61% organizations use 4 or more and 86% organizations 2 or more (anecdotal evidence based on […].

Business Intelligence 93

Business Intelligence Enterprise Reporting Data Governance 93

Analytics Vidhya

AUGUST 4, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction OpenCV is a great tool to play with images and. The post Getting Started With Object Tracking Using OpenCV appeared first on Analytics Vidhya.

Data Science 380

Data Science Publishing Analytics 380

Cloudera

AUGUST 4, 2021

Historically, maintenance has been driven by a preventative schedule. Today, preventative maintenance, where actions are performed regardless of actual condition, is giving way to Predictive, or Condition-Based, maintenance, where actions are based on actual, real-time insights into operating conditions. While both are far superior to traditional Corrective maintenance (action only after a piece of equipment fails), Predictive is by far the most effective.

IoT 98

IoT Unstructured Data Machine Learning Predictive Modeling 98

Speaker: Nicholas Zeisler, CX Strategist & Fractional CXO

The first step in a successful Customer Experience endeavor (or for that matter, any business proposition) is to find out what’s wrong. If you can’t identify it, you can’t fix it! 💡 That’s where the Voice of the Customer (VoC) comes in. Today, far too many brands do VoC simply because that’s what they think they’re supposed to do; that’s what all their competitors do.

Customer Analytics

FineReport

AUGUST 2, 2021

Business intelligence for marketing is the application of business intelligence in the field of marketing, allowing marketers to collect data, debugging data and processing it out through enterprise resource planning and company strategy. How BI can be applied to marketing? With the rapid development of Internet and changes of IT technology, marketing becomes a data-driven industry which requires fast data processing and intuitive demonstration.

Business Intelligence 92

Business Intelligence Marketing Slice and Dice Dashboards 92

Domino Data Lab

AUGUST 6, 2021

Data science is an incredibly complex field. When you factor in the requirements of a business-critical machine learning model in a working enterprise environment, the old cat-herding meme won’t even get a smile. Framing data science projects within the four steps of the data science lifecycle (DSLC) makes it much easier to manage limited resources and control timelines, while ensuring projects meet or exceed the business requirements they were designed for. 4 Steps in the DSLC.

Data Science 75

Data Science Testing Modeling Publishing 75

Analytics Vidhya

AUGUST 5, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon The focus of Computer vision is surrounded by the extraction of. The post Edge & Contour Detection – An application of Computer Vision appeared first on Analytics Vidhya.

Data Science 373

Data Science Publishing Analytics Structured Data 373

Dataiku

AUGUST 4, 2021

Only about five years ago, data preparation took up to 80% of time dedicated to a data project. In 2020, an Anaconda survey found that data scientists now spend about 45% of their time on data preparation tasks, including loading and cleaning data. While this is a significant improvement, data preparation remains a time-consuming step that needs to be optimized in order to scale AI across the organization and complete more projects faster.

Business Analysis 75

Business Analysis Optimization 75

Speaker: Jon Harmer, Product Manager for Google Cloud

Move from feature factory to customer outcomes and drive impact in your business! This session will provide you with a comprehensive set of tools to help you develop impactful products by shifting from output-based thinking to outcome-based thinking. You will deepen your understanding of your customers and their needs as well as identifying and de-risking the different kinds of hypotheses built into your roadmap.

Risk

TDAN

AUGUST 3, 2021

Artificial Technology has left groundbreaking improvements in several industries, and the health industry is no exception. In conjunction with machine learning, AI has been used in a myriad of ways to create a positive impact in our day-to-day lives. From telehealth to remote medical care and advanced appointment setting options such as AI-assisted diagnoses, the […].

Technology 59

Technology Machine Learning Business Intelligence Big Data 59

Domino Data Lab

AUGUST 6, 2021

Model Risk Management is about reducing bad consequences of decisions caused by trusting incorrect or misused model outputs. An enterprise starts by using a framework to formalize its processes and procedures, which gets increasingly difficult as data science programs grow. Systematically enabling model development and production deployment at scale entails use of an Enterprise MLOps platform, which addresses the full lifecycle including Model Risk Management.

Risk Management 64

Risk Management Risk Modeling Enterprise 64

Analytics Vidhya

AUGUST 2, 2021

ArticleVideo Book This article was published as a part of the Data Science Blogathon Introduction In computer vision, we have a convolutional neural network that. The post Image Classification Using CNN -Understanding Computer Vision appeared first on Analytics Vidhya.

Data Science 373

Data Science Publishing Analytics Unstructured Data 373

Dataiku

AUGUST 3, 2021

Augmented intelligence is all about bringing together the power and strengths of AI with those of humans by integrating AI systems into the day-to-day work of people to help them make better decisions. While augmented intelligence is easy to understand in theory, many organizations struggle to implement it in practice and at scale — here are three real-word examples of augmented intelligence.

IT 64

IT 64

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Strategy