Sat.Oct 02, 2021 - Fri.Oct 08, 2021

article thumbnail

Combining Empathy and AI

DataRobot

Trust in AI must be earned. Ideally, business users or consumers that interact with a model and its output displayed in a dashboard should not need to question its authenticity. Unfortunately, we aren’t there yet, and it’s because there are different components to trust, some we have yet to address. One of these components is empathy. Many individuals do not fully trust AI due to the lack of empathy that is instilled into models.

article thumbnail

A Beginner’s Guide to Feature Engineering – Everything You Need to Know!

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview Say, you were setting up a gift shop and your supplier dumps all the toys that you asked for in a room. It’s going to look something like this. Total chaos! Now picture yourself standing in front of this huge pile of toys […]. The post A Beginner’s Guide to Feature Engineering – Everything You Need to Know!

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

Alteryx Tackles Analytics Ops

David Menninger's Analyst Perspectives

Alteryx is a data analytics software company that offers data preparation and analytics tools to simplify and automate data wrangling, data cleaning and modeling processes, enabling line-of-business personnel to quickly access, manipulate, analyze and output data. The platform features tools to run a variety of analytic functions such as diagnostic, predictive, prescriptive and geospatial analytics in a unified platform, and can connect to various data warehouses, cloud applications, spreadsheet

Analytics 288
article thumbnail

DataOps Lowers The Cost Of Asking Analytic Questions

DataKitchen

The post DataOps Lowers The Cost Of Asking Analytic Questions first appeared on DataKitchen.

Analytics 246
article thumbnail

State of AI in Sales & Marketing 2025

AI adoption is reshaping sales and marketing. But is it delivering real results? We surveyed 1,000+ GTM professionals to find out. The data is clear: AI users report 47% higher productivity and an average of 12 hours saved per week. But leaders say mainstream AI tools still fall short on accuracy and business impact. Download the full report today to see how AI is being used — and where go-to-market professionals think there are gaps and opportunities.

article thumbnail

20 Best Examples of Charts and Graphs

Juice Analytics

We’ve collected these high-quality examples of charts and graphs to help you learn from the best. For each example, we point out some of the smart design decisions that make them effective in communicating the data. There is a lot of variety in styles and structures, but you may notice common elements across these well-designed data visualizations. For example, you’ll see… Thoughtful use of color; Few distracting elements that undermine the message; Labels and legends that highlight how to inter

article thumbnail

End-to-End Introduction to Handling Missing Values

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview Data provides us with the power to analyze and forecast the events of the future. With each day, more and more companies are adopting data science techniques like predictive forecasting, clustering, and so on. While it’s very intriguing to keep learning about complex […].

More Trending

article thumbnail

How Predictive and Prescriptive Analytics Improve the Call Center Experience

DataKitchen

The post How Predictive and Prescriptive Analytics Improve the Call Center Experience first appeared on DataKitchen.

article thumbnail

Deep Learning for Time Series Forecasting: Is It Worth It?

Dataiku

Using RNNs & DeepAR Models to Find Out. Time series forecasting use cases are certainly the most common time series use cases, as they can be found in all types of industries and in various contexts. Whether it is forecasting future sales to optimize inventory, predicting energy consumption to adapt production levels, or estimating the number of airline passengers to ensure high-quality services, time is a key variable.

article thumbnail

Introduction to Deep Learning in Julia

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview In the current scenario, the Data science field is dominated by Python/R but there is another competition added not so long ago, Julia! which we will be exploring in this guide. The famous quote (motto) of Julia is – Looks like Python, runs […]. The post Introduction to Deep Learning in Julia appeared first on Analytics Vidhya.

article thumbnail

Server Management Best Practices for Data-Driven Organizations

Smart Data Collective

There is no denying the fact that big data has become a critical asset to countless organizations all over the world. Many companies are storing data internally, which means that they have to be responsible for maintaining their own standards. Unfortunately, managing your own data server can be overwhelming. You have to make sure that your data is going to be secure from breaches and preserved from potential data outages.

article thumbnail

How to Achieve High-Accuracy Results When Using LLMs

Speaker: Ben Epstein, Stealth Founder & CTO | Tony Karrer, Founder & CTO, Aggregage

When tasked with building a fundamentally new product line with deeper insights than previously achievable for a high-value client, Ben Epstein and his team faced a significant challenge: how to harness LLMs to produce consistent, high-accuracy outputs at scale. In this new session, Ben will share how he and his team engineered a system (based on proven software engineering approaches) that employs reproducible test variations (via temperature 0 and fixed seeds), and enables non-LLM evaluation m

article thumbnail

Why Enterprise AI Needs Human Intervention

DataKitchen

The post Why Enterprise AI Needs Human Intervention first appeared on DataKitchen.

article thumbnail

BPMN Diagrams For Dummies

BA Learnings

What Is BPMN? Business process modeling notation, or BPMN, is the way BPM professionals communicate the design of a specific process, be it simple or exceedingly complex. There are various steps in any process that may come up, and notation helps a business process management (BPM) professional identify these at a glance, and to describe what needs to be done at any given point during the process based on element types.

Metrics 130
article thumbnail

Applications of Convolutional Neural Networks(CNN)

Analytics Vidhya

This article was published as a part of the Data Science Blogathon What is CNN? Convolutional Neural Network is a type of deep learning neural network that is artificial. It is employed in computer vision and image recognition. This procedure includes the following steps: OCR and image recognition Detecting objects in self-driving cars Social media face […].

article thumbnail

Benefits of Using Drupal to Create a Website with AI Capabilities

Smart Data Collective

AI technology has become a gamechanger for website development. Many developers are using AI to create better sites. However, it is also important to create sites with great AI features. AI-based solutions are becoming more and more popular among various industries. AI features can significantly improve the quality of your customer service and provide you with useful business insights.

article thumbnail

Zero Trust Mandate: The Realities, Requirements and Roadmap

The DHS compliance audit clock is ticking on Zero Trust. Government agencies can no longer ignore or delay their Zero Trust initiatives. During this virtual panel discussion—featuring Kelly Fuller Gordon, Founder and CEO of RisX, Chris Wild, Zero Trust subject matter expert at Zermount, Inc., and Principal of Cybersecurity Practice at Eliassen Group, Trey Gannon—you’ll gain a detailed understanding of the Federal Zero Trust mandate, its requirements, milestones, and deadlines.

article thumbnail

What is a DataOps Engineer?

DataKitchen

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. Data operations (or data production) is a series of pipeline procedures that take raw data, progress through a series of processing and transformation steps, and output finished products in the form of dashboards, predictions, data warehouses or whatever the business requires.

Testing 162
article thumbnail

Introducing New Enhancements to the Cloudera Connect Partner Program

Cloudera

October sees the launch of Partner Appreciation Month and during the next few weeks we will be sharing success stories, updates and interviews with our valued partners across the world. . We’re on a mission to make data and analytics easy and accessible, for everyone, and the hybrid data cloud is how we’ll get there. Today’s world is a hybrid world—there’s hybrid data, hybrid infrastructure, hybrid work—and leading businesses are embracing these changes, unafraid to transform their processes and

Sales 105
article thumbnail

A Comprehensive Guide on Market Basket Analysis

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview This comprehensive guide will instigate you to the world of Market Basket Analysis along with an implementation using Python on a dataset. Market Basket Analysis will help you to design different store Layouts. Introduction Nowadays Machine Learning is helping the Retail Industry in […].

Marketing 361
article thumbnail

The Evolving Importance of Analytics in Generating Leads through PPC

Smart Data Collective

Analytics technology has been invaluable to modern marketing. The market for web analytics is projected to be worth $9.11 billion by 2025. The utilization of analytics and big data in the marketing industry has played a massive role in this robust growth. One of the most important benefits of analytics in marketing is with PPC marketing. More companies are using analytics to expand the reach of their PPC campaigns and improve their ROI.

Analytics 133
article thumbnail

Revolutionize QA: GAPs AI-Driven Accelerators for Smarter, Faster Testing

GAP's AI-Driven QA Accelerators revolutionize software testing by automating repetitive tasks and enhancing test coverage. From generating test cases and Cypress code to AI-powered code reviews and detailed defect reports, our platform streamlines QA processes, saving time and resources. Accelerate API testing with Pytest-based cases and boost accuracy while reducing human error.

article thumbnail

Why the Conversation Is Shifting From Collaborative Data Science to Systemization

Dataiku

Collaboration has always been an integral element of successful data science, but the concept moved into the spotlight as the global health crisis swiftly shifted the dynamics of data teams everywhere — in the blink of an eye, they were forced to navigate their data science projects (both those that were in progress and that hadn’t begun yet) in a remote world.

article thumbnail

Take Advantage Of Strategic Dashboard – Read These 8 Tips

FineReport

There are three types of dashboards: operational, strategic, and analytical. We have discussed operational dashboards before. Today, I’m going to share more detailed information on strategic dashboards with you. This post will cover the definition, importance, and designing guide on strategic dashboards. Strategic dashboard. What is a strategic dashboard?

article thumbnail

Would you like to start your Machine Learning journey for FREE?

Analytics Vidhya

We live in an era where choices are just endless. Especially with respect to Education! With a plethora of data science courses online, it is difficult to identify where to begin your journey from. How about beginning your MACHINE LEARNING Journey FREE of charge? Since its inception, Analytics Vidhya has been striving hard to explain […]. The post Would you like to start your Machine Learning journey for FREE?

article thumbnail

How To Maintain Accurate Data Through Conversational Analysis?

Smart Data Collective

There is no question that big data is very important for many businesses. Unfortunately, big data is only as useful as it is accurate. Data quality issues can cause serious problems in your big data strategy. Customers won’t always directly tell you the information your company needs to provide better products or services. However, their conversations on social media, most frequently posted topics and words, and responses to survey questions can reveal information essential to your company’s per

Big Data 133
article thumbnail

The GTM Intelligence Era: ZoomInfo 2025 Customer Impact Report

ZoomInfo customers aren’t just selling — they’re winning. Revenue teams using our Go-To-Market Intelligence platform grew pipeline by 32%, increased deal sizes by 40%, and booked 55% more meetings. Download this report to see what 11,000+ customers say about our Go-To-Market Intelligence platform and how it impacts their bottom line. The data speaks for itself!

article thumbnail

NXP: Building a Data Organization That Performs & Elevates the Individual

Dataiku

The concept of AI in the enterprise has been around for a bit now, and the way different organizations have handled the implementation of data structures and management, as well as new evolutions in AI technology itself, varies greatly. Whether organizations are just now jumping into the game, or if they have benched their programs after finding themselves lost and confused in devising a strategy, many could benefit from studying an application approach such as NXP’s.

Strategy 104
article thumbnail

Everything is Connected, Everything Changes

Alation

Jason McVay is a data scientist at Indigo Ag, an agriculture-tech company headquartered in Massachusetts. He has an education in environmental science and geography, with a Master’s degree in paleoecology. In this essay, Jason reflects on the value of thinking spatially about data, showing how his experience as a graduate student influences his role as a data scientist today.

article thumbnail

Introduction to the Lifecycle of Data Science project

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Image Source: [link] Overview of Lifecycle of Data Science Project With the increasing demand for Data Scientists, more people are willing to enter into this field. It has become very important to showcase the right skills for Data Science to stand out from the […]. The post Introduction to the Lifecycle of Data Science project appeared first on Analytics Vidhya.

article thumbnail

How Genetic Algorithms and Machine Learning Apply to Investments

Smart Data Collective

Learn how genetic algorithms and machine learning can help hedge fund organizations manage a business. As well as bolster investor confidence and improve profitability. As a hedge fund shareholder, you certainly want the best for your organization, right? For instance, you want to generate effective AUM, NAV, and share value reports to improve investor confidence as a manager.

article thumbnail

Optimizing The Modern Developer Experience with Coder

Many software teams have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth. This is where Coder comes in. In our 101 Coder webinar, you’ll explore how cloud-based development environments can unlock new levels of productivity. Discover how to transition from local setups to a secure, cloud-powered ecosystem with ease.

article thumbnail

Volkswagen and Teradata Develop New Smart Factory Solution

Teradata

An interdisciplinary team from Volkswagen, AWS and Teradata have created an intelligent solution that enables greater transparency and efficiency in car body construction. Find out more.

98
article thumbnail

How to Select Data Catalog Software for Business Intelligence

Octopai

Finally. FINALLY. Your CFO finally gave the okay to purchase data catalog software. Wa-hoo! When you’ve cleaned up the confetti and the cocktail glasses, it’s time to get down to business. This is a major investment. How will you choose the best data catalog software for your company? Lest the proliferation of data catalog features and options leave you groping for someone’s leftover margarita, here’s a guide with the questions to ask to cut through the overwhelm and reach clarity. .

article thumbnail

A Comprehensive Guide to Reinforcement Learning

Analytics Vidhya

This article was published as a part of the Data Science Blogathon Overview Reinforcement learning is not just used for Robotics but now even in Data Science It has tons of applications and we will cover some of them in this guide. This comprehensive guide will introduce you to RL theory and implementation, all in Python […]. The post A Comprehensive Guide to Reinforcement Learning appeared first on Analytics Vidhya.

article thumbnail

An Introduction to Ranger RMS

Cloudera

Cloudera Data Platform (CDP) supports access controls on tables and columns, as well as on files and directories via Apache Ranger since its first release. It is common to have different workloads using the same data – some require authorizations at the table level (Apache Hive queries) and others at the underlying files (Apache Spark jobs). Unfortunately, in such instances you would have to create and maintain separate Ranger policies for both Hive and HDFS, that correspond to each othe

article thumbnail

15 Modern Use Cases for Enterprise Business Intelligence

Large enterprises face unique challenges in optimizing their Business Intelligence (BI) output due to the sheer scale and complexity of their operations. Unlike smaller organizations, where basic BI features and simple dashboards might suffice, enterprises must manage vast amounts of data from diverse sources. What are the top modern BI use cases for enterprise businesses to help you get a leg up on the competition?