January, 2023

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CIOs sharpen tech strategies to support hybrid work

CIO Business Intelligence

A significant number of organizations are operating in a hybrid model — and expect to continue with that hybrid environment for the foreseeable future. Global analytics and advice firm Gallup has found that the percentage of remote-capable workers working in a hybrid environment increased in 2022 , moving from 42% in February to 49% in June. Gallup also found that only 20% of remote-capable employees were working fully on-site while 30% were fully remote in 2022.

Strategy 142
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What is Data Quality in Machine Learning?

Analytics Vidhya

Introduction Machine learning has become an essential tool for organizations of all sizes to gain insights and make data-driven decisions. However, the success of ML projects is heavily dependent on the quality of data used to train models. Poor data quality can lead to inaccurate predictions and poor model performance. Understanding the importance of data […] The post What is Data Quality in Machine Learning?

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Free Data Management with Data Science Learning with CS639

KDnuggets

Learn Data Management with Data Science for FREE with CS639.

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What is business intelligence? Transforming data into business insights

CIO Business Intelligence

Business intelligence definition Business intelligence (BI) is a set of strategies and technologies enterprises use to analyze business information and transform it into actionable insights that inform strategic and tactical business decisions. BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts, and maps to provide users with detailed intelligence about the state of the business.

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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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7 tell-tale signs of fake DevOps

CIO Business Intelligence

There’s no doubt that DevOps has helped many IT organizations achieve their goal of delivering applications and services faster and better than traditional software development processes. Unfortunately, while some IT leaders do a fine job of trumpeting DevOps’ benefits, their teams are headed in the wrong direction , embracing half-baked or completely wrong tools and practices.

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From Data Collection to Model Deployment: 6 Stages of a Data Science Project

KDnuggets

Here are 6 stages of a novel Data Science Project; From Data Collection to Model in Production, backed by research and examples.

More Trending

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Roadmap to Adopting and Implementing MLOps in Organizations

Analytics Vidhya

Introduction Welcome to the world of MLOps, or Machine Learning Operations! If you’re an industry specialist looking to understand MLOps and how it can benefit your organization, then you’re at the right place. MLOps, or Machine Learning Operations, is a set of practices and techniques that enables an organization to effectively build, deploy, and manage […].

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Use this Strategic Approach to Maximize Your Data’s Value

Smart Data Collective

In today’s world, data is more widely available to businesses than ever before. Whether it’s data about customer demographics , product colors that tend to sell better, or which cold email scripts are the most effective, organizations have the power to utilize data to help them inform their decision-making process in a variety of ways. However, while the immense amount of data available to organizations unlocks new possibilities — it can also make cleaning organizing, interpreting, and analyzing

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Introducing native support for Apache Hudi, Delta Lake, and Apache Iceberg on AWS Glue for Apache Spark, Part 1: Getting Started

AWS Big Data

AWS Glue is a serverless, scalable data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources. AWS Glue provides an extensible architecture that enables users with different data processing use cases. A common use case is building data lakes on Amazon Simple Storage Service (Amazon S3) using AWS Glue extract, transform, and load (ETL) jobs.

Data Lake 116
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Top automation pitfalls and how to avoid them

CIO Business Intelligence

First Tech Credit Union is a San Jose-based financial institution with more than $16 billion in assets. As the eighth largest in the country, it primarily serves tech companies and their employees, but still has a lot of manual processes in place. “We’re very early in our automation journey,” says Mike Upton, the organization’s digital and technology officer.

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Driving Business Impact for PMs

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.

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Top 10 Charts in 2022

The Data Visualisation Catalogue

As per tradition, the website stats on the most popular chart reference pages for the past year are made public for all readers of this website to explore. As usual, the data is taken from 1st January 2022 to 31st December 2022 for only the English site, with any previously mentioned years following the same date range. Below is the list for the Top-10 chart reference pages for 2022: But how does this list compare to last year’s Top 10?

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ChatGPT as a Python Programming Assistant

KDnuggets

Is ChatGPT useful for Python programmers, specifically those of us who use Python for data processing, data cleaning, and building machine learning models? Let's give it a try and find out.

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Machine Learning Solution Predicting Road Accident Severity

Analytics Vidhya

This article was published as a part of the Data Science Blogathon. Introduction This is a multiclass classification project to classify the severity of road accidents into three categories. This project is based on real-world data, and the dataset is also highly imbalanced. There are three types of injuries in a target variable: minor, severe, […].

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6 Tips for Using Data Analytics for Product Page SEO

Smart Data Collective

Data analytics technology is becoming more important for marketing than ever before. Companies are projected to spend over $27 billion on marketing analytics by 2031. One of the many ways that marketers are leveraging data analytics is SEO. Data-driven SEO can be very beneficial for any company trying to boost organic search traffic to their product pages.

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Entity Resolution Checklist: What to Consider When Evaluating Options

Are you trying to decide which entity resolution capabilities you need? It can be confusing to determine which features are most important for your project. And sometimes key features are overlooked. Get the Entity Resolution Evaluation Checklist to make sure you’ve thought of everything to make your project a success! The list was created by Senzing’s team of leading entity resolution experts, based on their real-world experience.

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Machine Learning to Improve SEO Performance

TDAN

For the larger part of my SEO career, I was leading a team of a dozen marketing specialists working on multiple SaaS or affiliate projects. At one point, I asked myself whether I could utilize my data science expertise to get better marketing results.

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Top 9 challenges IT leaders will face in 2023

CIO Business Intelligence

Three years ago, IT leaders were squarely focused on how to adopt fledgling AI techniques and approaches into their business models in service of digital transformations that included plans for shifting some workloads to the cloud. But then the pandemic hit, requiring a historic pivot that set some best-laid plans aside and accelerated others. Now that organizations have returned to a new (somewhat) normal, CIOs appear to be focused on getting back to basics — and untangling tech debt incurred i

IT 145
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Making the Most of Qualitative Data: The Story of Text Explorer

Dataiku

This is a guest post by Adam McMaster and Meirin Evans, our friends at The Brilliant Club, whom we have partnered with since 2021. Adam joined The Brilliant Club in October 2022 for a three-month internship as part of his doctoral training program. Adam is in the third year of his Ph.D. at the Open University and his research focuses on black holes and variable stars.

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Where Collaboration Fails Around Data (And 4 Tips for Fixing It)

KDnuggets

Data-driven organizations require complex collaboration between data teams and business stakeholders. Here are 4 proactive tips for reducing information asymmetries and achieving better collaboration.

IT 159
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The Big Payoff of Application Analytics

Outdated or absent analytics won’t cut it in today’s data-driven applications – not for your end users, your development team, or your business. That’s what drove the five companies in this e-book to change their approach to analytics. Download this e-book to learn about the unique problems each company faced and how they achieved huge returns beyond expectation by embedding analytics into applications.

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Introduction to Redis OM in Python

Analytics Vidhya

Introduction Redis OM is a widely used in-memory database deployed as a cache or database and message broker. It is well-suited for high-performance, real-time applications that need low-latency data access. Redis supports several data types, including strings, lists, sets, and hyperloglogs. Redis-py is one of the most used Redis Clients for python to access the Redis […] The post Introduction to Redis OM in Python appeared first on Analytics Vidhya.

Analytics 349
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7 Mistakes to Avoid When Using Machine Learning for SEO

Smart Data Collective

Companies around the world are projected to spend over $300 billion on machine learning technology by 2030. There are a growing number of reasons that companies are investing in machine learning, but digital marketing is at the top of the list. SEO, in particular, relies more heavily on machine learning these days. More Companies Are Discovering the Benefits of Using Machine Learning for SEO A few years ago, we wrote an article pointing out that machine learning is rewriting the rules of SEO.

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A Step Ahead: Federated Data Stores

TDAN

Government systems produce and store a large amount of data daily. Government leaders want to utilize this data to make decisions faster and more efficiently. It is nearly impossible to make well-informed decisions if that data is not visible, accessible, organized, and cannot be seamlessly discovered across the enterprise.

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The 7 new rules of IT leadership

CIO Business Intelligence

The CIO role continues to evolve, changing as dramatically as the technology it manages and maintains. Moreover, the pace of the chief IT position’s transformation seems to be accelerating — likewise mirroring the speed of change in the tech stack. Consequently, tech executives must lead, manage, and work differently than they did in the past. How so?

IT 145
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Your Expert Guide to CX Orchestration & Enhancing Customer Journeys

Speaker: Keith Kmett, Principal CX Advisor at Medallia

Join Keith Kmett, Principal CX Advisor, in this new webinar that will focus on: Understanding CX Orchestration Fundamentals: Gain a solid understanding of what CX orchestration is, its significance in the customer experience landscape, and how it plays a crucial role in shaping customer journeys. This includes the key concepts, strategies, and best practices involved in CX orchestration. 🔑 Connection to Customer Journey Maps: How to effectively integrate customer journey mapping into the

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Why Is Data Architecture Important for the Success of AI?

Dataiku

If there’s one thing we’ve learned at Dataiku after talking to thousands of prospects and customers about their data architecture it’s that architecture frameworks tend to be more aspirational than realistic because, at the enterprise level, data architecture is both complex and constantly changing. But the importance of data architecture in the success of AI initiatives at an organization also cannot be understated.

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Python Matplotlib Cheat Sheets

KDnuggets

Matplotlib is the most famous and commonly used plotting library in Python. It allows you to create clear and interactive visualizations that make your data easier to understand and your results more concrete.

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How is TinyML Used for Embedding Smaller Systems?

Analytics Vidhya

Introduction There are many emerging trends in the tech world, and Machine Learning is one of them. Machine Learning is a subset of Artificial Intelligence where a computer learns from data and analyses its patterns to predict an outcome. Usually, Machine Learning models are trained on big chunks of data to analyze the patterns where […] The post How is TinyML Used for Embedding Smaller Systems?

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Data Visualization Boosts Business Scalability with Sales Mapping

Smart Data Collective

Data visualization tools have become very useful for many businesses. Companies use data visualization for trend mapping, data contextualization and various forms of business optimization. Therefore, it should come as no surprise that global companies are projected to spend over $10.2 billion on data visualization technology within the next three years.

Sales 114
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Addressing Top Enterprise Challenges in Generative AI with DataRobot

The buzz around generative AI shows no sign of abating in the foreseeable future. Enterprise interest in the technology is high, and the market is expected to gain momentum as organizations move from prototypes to actual project deployments. Ultimately, the market will demand an extensive ecosystem, and tools will need to streamline data and model utilization and management across multiple environments.

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What’s Your Data Culture Plan for 2023?

TDAN

As we start the new year, it is a good chance for us to take a step back and re-think how we are approaching our data culture. How are we improving data trust? Are we being intentional about our data communications? Are we supported by senior leadership? Every organization has a data culture: the organizational […].

IT 98
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8 top priorities for CIOs in 2023

CIO Business Intelligence

Welcome to 2023. As the new year arrives, CIOs are facing a challenging to-do list as they strive to maximize IT productivity and efficiency in increasingly unpredictable times. As technology projects, budgets, and staffing grew over the past few years, the focus was on speed to market to maximize opportunity, says Troy Gibson, CIO services leader at business and IT advisory firm Centric Consulting.

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Scaling AI/ML Success: Key Components of a Future-Proof Platform

Dataiku

Not long ago, just having a data science team allowed executives to say they were "doing AI," but that has changed. In the past few years, companies across industries have used machine learning (ML) and AI technologies to streamline processes and improve experiences leading to increased revenues at lower costs. These achievements have made advanced analytics and AI an essential technology, and IT leaders are taking AI projects into mainstream IT programs at scale.

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5 Ways to Deal with the Lack of Data in Machine Learning

KDnuggets

Effective solutions exist when you don't have enough data for your models. While there is no perfect approach, five proven ways will get your model to production.

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Reimagined: Building Products with Generative AI

“Reimagined: Building Products with Generative AI” is an extensive guide for integrating generative AI into product strategy and careers featuring over 150 real-world examples, 30 case studies, and 20+ frameworks, and endorsed by over 20 leading AI and product executives, inventors, entrepreneurs, and researchers.