Sat.Sep 28, 2024 - Fri.Oct 04, 2024

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3 things to get right with data management for gen AI projects

CIO Business Intelligence

According to Kari Briski, VP of AI models, software, and services at Nvidia, successfully implementing gen AI hinges on effective data management and evaluating how different models work together to serve a specific use case. While a few elite organizations like Nvidia use gen AI for things like designing new chips, most have settled on less sophisticated use cases that employ simpler models, and can focus on achieving excellence in data management.

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Implementing Data Governance in Data Science Pipelines: Techniques and Best Practices

KDnuggets

Discover the keys for a successful adoption of data governance schemes in your data science projects.

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7 LLM Parameters to Enhance Model Performance (With Practical Implementation)

Analytics Vidhya

Introduction Let’s say you’re interacting with an AI that not only answers your questions but understands the nuances of your intent. It crafts tailored, coherent responses that almost feel human. How does this happen? Most people don’t even realize the secret lies in LLM parameters. If you’ve ever wondered how AI models like ChatGPT generate […] The post 7 LLM Parameters to Enhance Model Performance (With Practical Implementation) appeared first on Analytics Vidhya.

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Active Data Architecture: The Need of the Hour

Data Virtualization

Reading Time: 3 minutes As organizations continue to pursue increasingly time-sensitive use-cases including customer 360° views, supply-chain logistics, and healthcare monitoring, they need their supporting data infrastructures to be increasingly flexible, adaptable, and scalable. Howard Dresner refers to such infrastructures as “active data architecture.

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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have migrated their testing and production workloads to the cloud, yet development environments often remain tied to outdated local setups, limiting efficiency and growth.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.

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Accelerate Amazon Redshift Data Lake queries with AWS Glue Data Catalog Column Statistics

AWS Big Data

Amazon Redshift enables you to efficiently query and retrieve structured and semi-structured data from open format files in Amazon S3 data lake without having to load the data into Amazon Redshift tables. Amazon Redshift extends SQL capabilities to your data lake, enabling you to run analytical queries. Amazon Redshift supports a wide variety of tabular data formats like CSV, JSON, Parquet, ORC and open tabular formats like Apache Hudi, Linux foundation Delta Lake and Apache Iceberg.

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T-SQL Tuesday #179: What’s In Your Data Detective Toolkit?

Tim Mitchell

Most of us who work with data have, at least a few times, been presented with a challenge to explore and attempt to make sense of a poorly-defined set of data. Often it’s a collection of text files or Excel documents without any context or documentation. In other cases, it’s a database with no data map or metadata to help. The post T-SQL Tuesday #179: What’s In Your Data Detective Toolkit?

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How to Apply Your Brand Colors in Dataviz

Depict Data Studio

Colors can make or break a chart. Colors direct our eye movements, and therefore our brains and attention. It’s up to you: will you help or hinder your reader’s understanding? Step 1: Start with Your Brand Colors Otherwise, your graphs, slides, and dashboards will be Frankensteined. I’ve written about brand colors and brand presents in other posts.

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ChatGPT and Other AI Startups Drive Software Engineer Demand

Smart Data Collective

AI technology has created many promising new opportunities for software engineers in recent years.

Software 106
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Data Crime: Cartoon Signatures

TDAN

I call it a “data crime” when someone is abusing or misusing data. When we understand these stories and their implications, it can help us learn from the mistakes and prevent future data crimes. The stories can also be helpful if you must explain the importance of  data management to someone.

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Key Challenges and Limitations in AI-Language Models

Analytics Vidhya

Introduction Artificial Intelligence has been cementing its position in workplaces over the past couple of years, with scientists spending heavily on AI research and improving it daily. AI is everywhere, from simple tasks like virtual chatbots to complex tasks like cancer detection. It has even recently replaced several jobs in the industry. This inclusion of […] The post Key Challenges and Limitations in AI-Language Models appeared first on Analytics Vidhya.

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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?

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7 Data Engineering Tools for Beginners

KDnuggets

Learn the data engineering tools for data orchestration, database management, batch processing, ETL (Extract, Transform, Load), data transformation, data visualization, and data streaming.

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How AI is transforming business today

CIO Business Intelligence

Hannah Calhoon, vice president of AI for Indeed, uses artificial intelligence “to make existing tasks faster, easier, higher quality and more effective.” She points to a recent initiative in which the job matching and hiring platform company started using large language models (LLMs) to add a highly customized sentence or two to the emails it sends to job seekers about open positions that match their qualifications.

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Data as a Product: Needs and Requirements

David Menninger's Analyst Perspectives

I previously wrote about data mesh as a cultural and organizational approach to distributed data processing. Data mesh has four key principles—domain-oriented ownership, data as a product, self-serve data infrastructure and federated governance—each of which is being widely adopted. I assert that by 2027, more than 6 in 10 enterprises will adopt technologies to facilitate the delivery of data as a product as they adapt their cultural and organizational approaches to data ownership in the context

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Understanding SciPy Library in Python

Analytics Vidhya

Introduction Suppose you are a scientist or an engineer solving numerous problems – ordinary differential equations, extremal problems, or Fourier analysis. Python is already your favorite type of language given its easy usage in graphics and simple coding ability. But now, these are complex enough tasks, and therefore, one requires a set of powerful tools. […] The post Understanding SciPy Library in Python appeared first on Analytics Vidhya.

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8 Steps to Transformation at Speed & Scale – Your Guide to Deploying StratOps

📌Is your Data & AI transformation struggling to really impact the business? Discover the game-changing StratOps approach that: Bridges the Gap : Connect your Data & AI strategy to your operating model, to ensure alignment at every level. Prioritizes Outcomes : Focuses on concrete business outcomes from day one, rather than capabilities in isolation.

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Building Command Line Apps in Python with Click

KDnuggets

Have you ever wondered how you can easily create command-line applications in Python? Gather yourself up because that is what I am going to cover today.

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Accenture forms new Nvidia business group focused on agentic AI adoption

CIO Business Intelligence

Accenture and Nvidia announced an expanded partnership Wednesday with Accenture’s new Nvidia business group focused on helping customers rapidly scale AI adoption. Accenture said the new group will use Accenture’s AI Refinery platform — built on the Nvidia AI stack, including Nvidia AI Foundry, Nvidia AI Enterprise, and Nvidia Omniverse — to help clients create a foundation for use of agentic AI.

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Deprecation of Lake Formation’s Governed Tables Feature

AWS Big Data

After careful consideration, we have made the decision to end support for Governed Tables , effective December 31, 2024, to focus on open source transactional table formats such as Apache Iceberg , Apache Hudi , and Linux Foundation Delta Lake. This decision stems from customer preference for these open source solutions, which offer ACID-compliant transactions, compaction, time travel, and other features previously provided by Governed Tables.

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Top 10 Reddit Threads on Generative AI

Analytics Vidhya

Introduction As generative AI continues to advance, discussions about its potential, challenges, and future developments are intensifying. Reddit, a platform recognized for its thorough and candid conversations, has become a popular space for users to exchange insights, critiques, and predictions about this revolutionary technology. In this article, we delve into the top 10 generative AI […] The post Top 10 Reddit Threads on Generative AI appeared first on Analytics Vidhya.

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Marketing Operations in 2025: A New Framework for Success

Speaker: Mike Rizzo, Founder & CEO, MarketingOps.com and Darrell Alfonso, Director of Marketing Strategy and Operations, Indeed.com

Though rarely in the spotlight, marketing operations are the backbone of the efficiency, scalability, and alignment that define top-performing marketing teams. In this exclusive webinar led by industry visionaries Mike Rizzo and Darrell Alfonso, we’re giving marketing operations the recognition they deserve! We will dive into the 7 P Model —a powerful framework designed to assess and optimize your marketing operations function.

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5 Common Data Science Resume Mistakes to Avoid

KDnuggets

Want to create data science resumes that land interview calls and jobs? Avoid these common mistakes.

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AI on the mainframe? IBM may be onto something

CIO Business Intelligence

CIOs have been moving workloads from legacy platforms to the cloud for more than a decade but the rush to AI may breathe new life into an old enterprise friend: the mainframe. At least IBM believes so. Rather than pull away from big iron in the AI era, Big Blue is leaning into it, with plans in 2025 to release its next-generation Z mainframe , with a Telum II processor and Spyre AI Accelerator Card, positioned to run large language models (LLMs) and machine learning models for fraud detection an

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Moving Beyond Guesswork: How to Evaluate LLM Quality

Dataiku

Ninety percent of leaders are already investing in Generative AI in some way, but there's a common challenge: How can you objectively measure whether an LLM's output is actually "good enough"? For instance, imagine you’re using an LLM to power a conversational Q&A chatbot. After a few successful exchanges, it’s tempting to assume the model is delivering high-quality answers, but how can you quantify and benchmark that?

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Top 8 Applications of RAGs in Workplaces

Analytics Vidhya

Introduction Retrieval-Augmented Generation (RAG) is one of the most exciting recent innovations in artificial intelligence (AI). RAGs combine the power of generative models, like GPT, with a retrieval system that searches for relevant information in real-time. This makes them highly effective tools for various job roles across various industries. Whether you’re a data scientist, a […] The post Top 8 Applications of RAGs in Workplaces appeared first on Analytics Vidhya.

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The Cloud Development Environment Adoption Report

Cloud Development Environments (CDEs) are changing how software teams work by moving development to the cloud. Our Cloud Development Environment Adoption Report gathers insights from 223 developers and business leaders, uncovering key trends in CDE adoption. With 66% of large organizations already using CDEs, these platforms are quickly becoming essential to modern development practices.

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Ultimate Roadmap to Becoming a Tech Professional with Harvard for Free

KDnuggets

Jumping into the technology world doesn’t have to be so daunting.

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EU taps AI experts to develop compliance framework for AI regulations

CIO Business Intelligence

The European Commission has appointed a group of AI specialists to outline how businesses should comply with forthcoming AI regulations. The group includes prominent figures like AI pioneer Yoshua Bengio, former UK government adviser Nitarshan Rajkumar, and Stanford University fellow Marietje Schaake. They will oversee four working groups, each focusing on different aspects of AI governance — transparency and copyright, risk identification and assessment, technical risk mitigation, and internal

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Build a dynamic rules engine with Amazon Managed Service for Apache Flink

AWS Big Data

Imagine you have some streaming data. It could be from an Internet of Things (IoT) sensor, log data ingestion, or even shopper impression data. Regardless of the source, you have been tasked with acting on the data—alerting or triggering when something occurs. Martin Fowler says : “You can build a simple rules engine yourself. All you need is to create a bunch of objects with conditions and actions, store them in a collection, and run through them to evaluate the conditions and execute the actio

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3 Ways to Run Llama 3.2 on Your Device

Analytics Vidhya

Introduction Meta recently launched Llama 3.2, its latest multimodal model. This version offers improved language understanding, provides more accurate answers and generates high-quality text. It can now analyze and interpret images, making it even more versatile in understanding and responding to various input types! Llama 3.2 is a powerful tool that can help you with […] The post 3 Ways to Run Llama 3.2 on Your Device appeared first on Analytics Vidhya.

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Prepare Now: 2025s Must-Know Trends For Product And Data Leaders

Speaker: Jay Allardyce, Deepak Vittal, Terrence Sheflin, and Mahyar Ghasemali

As we look ahead to 2025, business intelligence and data analytics are set to play pivotal roles in shaping success. Organizations are already starting to face a host of transformative trends as the year comes to a close, including the integration of AI in data analytics, an increased emphasis on real-time data insights, and the growing importance of user experience in BI solutions.

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Do We Really Need More Complex Models?

KDnuggets

Simplicity might be a better solution.

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74% of workers suggest employers to blame for their AI skills gap

CIO Business Intelligence

AI is top of mind for workers who have an eye on how the technology will impact their day-to-day jobs and long-term career prospects. And for good reason as 92% of IT jobs are expected to be transformed by AI , rendering 74% of IT pros fearful that AI will make their skills obsolete. A recent survey from Skillsoft sheds additional light on these dynamics.

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SAP Clean Core Disrupts DevOps AI Development

Smart Data Collective

SAP Clean Core is great for AI software developers trying to create powerful machine learning programs.

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Understanding SQL WHERE Clause

Analytics Vidhya

Introduction The WHERE clause is an essential component that is used in SQL statements. This option is used for filtering records in order to give out specific data from the database files. Suppose you have a huge list of customers storing their information in your database; you need to search for customers from a specific […] The post Understanding SQL WHERE Clause appeared first on Analytics Vidhya.

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The Ultimate Guide To Data-Driven Construction: Optimize Projects, Reduce Risks, & Boost Innovation

Speaker: Donna Laquidara-Carr, PhD, LEED AP, Industry Insights Research Director at Dodge Construction Network

In today’s construction market, owners, construction managers, and contractors must navigate increasing challenges, from cost management to project delays. Fortunately, digital tools now offer valuable insights to help mitigate these risks. However, the sheer volume of tools and the complexity of leveraging their data effectively can be daunting. That’s where data-driven construction comes in.