Thu.Dec 07, 2023

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Here’s How You May Start Using Google’s Gemini?

Analytics Vidhya

Step into the future of conversational AI with Google’s Gemini AI, a model offering unparalleled capabilities in understanding, summarizing, reasoning, coding, and planning. In this article, we’ll talk about how you may start using Gemini AI right now, within Google’s Bard chatbot, unlocking new dimensions of interactive and refined chat experiences.

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ON DEMAND WEBINAR: Beyond Data Observability

DataKitchen

Do you have data quality issues, a complex technical environment, and a lack of visibility into production systems? These challenges lead to poor quality analytics and frustrated end users. Getting your data reliable is a start, but many other problems arise even if your data could be better. And your customers don't care where the problem is in your toolchain.

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ChatGPT vs Gemini : A Clash of the Titans in the AI Arena

Analytics Vidhya

Introduction Artificial intelligence has witnessed a captivating duel unfold between two titans – Google’s Gemini AI and OpenAI’s ChatGPT. While ChatGPT has enjoyed the spotlight, Gemini AI has quietly built its arsenal, waiting for the opportune moment to strike. And strike it did, unleashing a barrage of impressive benchmarks that have shaken the very foundation […] The post ChatGPT vs Gemini : A Clash of the Titans in the AI Arena appeared first on Analytics Vidhya.

Analytics 337
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Talk Directly to Your Data Using Everyday Language

KDnuggets

DataGPT is a conversational AI data analytics software provider that delivers analysis at the speed of business questions. DataGPT empowers anyone, in any company, to talk directly to their data using everyday language, revealing expert answers to complex questions instantly.

Software 123
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How To Get Promoted In Product Management

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.

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10 Ways to Automate Your Tasks Using Autonomous AI Agents

Analytics Vidhya

Introduction In the dynamic landscape of technology, autonomous AI agents have emerged as transformative entities, reshaping the way we interact with data and artificial intelligence. As we delve into this fascinating realm, it becomes evident that these agents are more than mere programs—they represent a paradigm shift in the integration of AI into our daily […] The post 10 Ways to Automate Your Tasks Using Autonomous AI Agents appeared first on Analytics Vidhya.

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How to create an effective business continuity plan

CIO Business Intelligence

The tumultuous events of the past several years have impacted practically every business. And with the number of extreme weather events, cyberattacks, and geopolitical conflicts continuing to rise, business leaders are bracing for the possibility of increasingly more frequent impactful incidents their organizations will need to respond to. According to PwC’s 2023 Global Crisis and Resilience Survey , 96% of 1,812 business leaders said their organizations had experienced disruption in the past tw

Testing 124

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When natural disasters strike Japan, ?ita University’s EDiSON is ready to act

CIO Business Intelligence

Over the centuries, Japan has endured more than its fair share of natural disasters – such as the Great Kanto earthquake of 1923 that resulted in close to 40,000 lives lost in downtown Tokyo alone and, more recently, the 2011 Tohoku quake and tsunami that devastated the northeast coast of Japan, killing 18,000 residents with approximately 20,000 more still uncounted for to this day.

IoT 108
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Jio’s Haptik Launches AI Tool for Business

Analytics Vidhya

On Wednesday, Haptik, Indian artificial intelligence startup, part of Reliance Jio Infocomm, introduced a specialized generative AI platform aimed at enabling business clients to build virtual assistants and backend information support. The platform, named ‘Contakt,’ is already doing initial pilot deployments, with the company expressing expectations for its expansion in the future.

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Using Google’s NotebookLM for Data Science: A Comprehensive Guide

KDnuggets

This blog post explores NotebookLM, its functionality, limitations, and advanced features essential for researchers and scientists.

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Unlocking the Gate to Data Science: Your Ultimate Study Guide for GATE 2024 in DS & AI

Analytics Vidhya

Introduction The Graduate Aptitude Test in Engineering (GATE) is an entrance examination conducted in India for postgraduate admission. The exam primarily tests the comprehensive understanding of undergraduate subjects in engineering and sciences. If you’re gearing up for the GATE 2024 in Data Science and AI, introduced by IISc Bangalore, you’re in the right place.

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Navigating the Future: Generative AI, Application Analytics, and Data

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?

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WestRock CIDO Amir Kazmi on building resiliency

CIO Business Intelligence

Amir Kazmi is a savvy business leader whose leadership playbook has been shaped by the fact that he’s spent one third of his career in P&L roles. In his current role as chief information and digital officer at WestRock, he’s responsible for developing and executing global information systems, technology, and cybersecurity strategy in addition to leading the company’s digital transformation.

Testing 105
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Understanding Code Golfing in Python

Analytics Vidhya

Introduction Code golfing is a fascinating concept in programming, where developers compete to write the shortest code to solve a given problem. It’s similar to a game where the object is to use the fewest letters possible to get the desired result. The methods, difficulties, advice, and best practices of Python code golfing will all […] The post Understanding Code Golfing in Python appeared first on Analytics Vidhya.

Analytics 270
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Top 10 Kaggle Machine Learning Projects to Become Data Scientist in 2024

KDnuggets

Master Data Science with Top 10 Kaggle ML Projects to become a Data Scientist.

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Smart Video Bloggers Are Leveraging Cloud-Based Marketing Tools

Smart Data Collective

Video blogging (which is often referred to as vlogging) has become a very popular medium for people that want to share their ideas and knowledge with people they would never otherwise reach.

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Get Better Network Graphs & Save Analysts Time

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.

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Unlocking generative AI’s greatest growth opportunities

CIO Business Intelligence

Over the last year, generative AI—a form of artificial intelligence that can compose original text, images, computer code, and other content—has gone from experimental curiosity to a tech revolution that could be one of the biggest business disruptors of our generation. Along the way, business leaders in every industry have been scrambling to develop their generative AI strategies, address potential risks, and figure out the best next action while trying to stay one step ahead of the competition

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Cracking the Code: How Dataiku's AI Assistant Upgrades Data Science Workflows

Dataiku

Full disclosure: As a citizen data scientist, I’ve never formally trained as a software developer or professional data engineer. However, I do have plenty of experience iterating through code until I meet my goals — whether that’s doing exploratory data analysis (EDA) in a notebook to understand a dataset, engineering features in preparation for machine learning, or reusing code someone else has written for a specific data task.

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Six ways AI can influence the future of customer service

IBM Big Data Hub

Organizations have always used some degree of technology to provide an excellent customer experience , but the future of customer service will demand even more advancements to meet customers’ growing expectations. There is no question that customer service is about to take a massive leap forward, thanks to emerging trends like artificial intelligence (AI).

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FinOps and the Denodo Platform: How To Optimize Cloud Data Costs

Data Virtualization

Reading Time: 4 minutes In recent years, the IT world has been steadily moving to the cloud. Many companies have migrated their data to the cloud, convinced that this step could have a substantial impact on managing costs. This, however, is an illusion, and. The post FinOps and the Denodo Platform: How To Optimize Cloud Data Costs appeared first on Data Management Blog - Data Integration and Modern Data Management Articles, Analysis and Information.

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How Embedded Analytics Gets You to Market Faster with a SAAS Offering

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.

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AWS Clean Rooms proof of concept scoping part 1: media measurement

AWS Big Data

Companies are increasingly seeking ways to complement their data with external business partners’ data to build, maintain, and enrich their holistic view of their business at the consumer level. AWS Clean Rooms helps companies more easily and securely analyze and collaborate on their collective datasets—without sharing or copying each other’s underlying data.

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Knowledge Graphs: Breaking the Ice

Ontotext

A graph is like a map that represents real-life objects and the relationships between them. While many of us use Google, Twitter, Alexa and Siri, likely most don’t know (or think about) that they are powered by knowledge graph technology. In these social network graphs, the objects are people and organizations, and the relationships are ‘follows’ or ‘friends’.

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Data center consolidation: Strategy and best practices

IBM Big Data Hub

The modern pace of data creation is staggering. The average organization produces data constantly—perhaps even continuously—and soon it’s investing in servers to provide ample storage for that information. In time, and probably sooner than expected, the organization accrues more data and outgrows that server, so it invests in multiple servers.

Strategy 103
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Cybersecurity for enterprise: 10 essential PAM considerations for modern hybrid enterprises

CIO Business Intelligence

Supporting enterprise security during a cloud migration can be rife with pitfalls that can derail the initiative and ruin the customer experience. It’s no joke—I know a finance director who suffered this fate. She joined the company in the middle of a corporate cloud transformation initiative and inherited a new Privileged Access Management (PAM) solution as part of an enterprise cybersecurity overhaul.

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Understanding User Needs and Satisfying Them

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.

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API-led connectivity: Improve API reuse and organizational agility

IBM Big Data Hub

Today’s customers and employees expect a real-time, personalized and connected user experience on any platform. As enterprise applications grow and evolve to address these needs, integration between applications has become increasingly important. Building point-to-point integrations manually is time consuming, inefficient and costly; andorganizations need a better way to consume and share data, as well as a more flexible and agile way to add new features and solutions.

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The data deluge: The need for IT Operations observability and strategies for achieving it

CIO Business Intelligence

To understand service health, IT needs to examine availability, security, performance, and log data from all layers of the ecosystem. Accomplishing this task requires observability driven by artificial intelligence (AI). Simply put, observability is the ability to look at data from all of an organization’s tools to understand the state of an application or service.

IT 107
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How OLAP and AI can enable better business

IBM Big Data Hub

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. OLAP systems are designed to efficiently process and analyze large multidimensional datasets, while AI techniques extract insights and make predictions from OLAP data.

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BMC on BMC: How the company enables IT observability with BMC Helix and AIOps

CIO Business Intelligence

As a global company with more than 6,000 employees, BMC faces many of the same data challenges that other large enterprises face. The organization has 500 applications for business services, 80,000 VMs, 3,000 hosts, and more than 100,000 containers. BMC needed a solution to transform this large volume of data and enable observability to understand thousands of events as a single scenario.

IT 105
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Embedding BI: Architectural Considerations and Technical Requirements

While data platforms, artificial intelligence (AI), machine learning (ML), and programming platforms have evolved to leverage big data and streaming data, the front-end user experience has not kept up. Holding onto old BI technology while everything else moves forward is holding back organizations. Traditional Business Intelligence (BI) aren’t built for modern data platforms and don’t work on modern architectures.