Data Science at Dow Jones: Monetizing Data, News and Information

•Download as PPT, PDF•

6 likes•1,415 views

O

In this presentation I will describe the way Data Science supports the business of information and news at Dow Jones. Specifically, I will describe how we are introducing innovative and advanced large-scale information mining and analytic approaches not only into Dow Jones’ products but also into our strategy and decision making processes.Our goal is to impact every aspect of Dow Jones: from the way journalism is produced in the newsroom, to the way we create and deliver institutional products, to the way we improve retention and acquisition of subscribers. While the task seems broad and daunting, we have already achieved various successes through the application of machine learning, data mining, advanced analytics and big data approaches.In this presentation I will describe how we have achieved this, including our tools, data, approaches and mechanisms as well as describe what our plans are going forward.

DATA SCIENCE AT DOW
JONES: MONETIZING
DATA, NEWS AND
INFORMATION
Juan M. Huerta
O P E N
D A T A
S C I E N C E
C O N F E R E N C E_
BOSTON
2015
@opendat
asci

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

Data Science at Dow Jones: Monetizing Data, News and Information

More Related Content

More from odsc

Have you been in the situation where you’re about to start a new project and ask yourself, what’s the right tool for the job here? I’ve been in that situation many times and thought it might be useful to share with you a recent project we did and why we selected Spark, Python, and Parquet. My plan is take you through a use case that involves loading, transforming, aggregating, and persisting the dataset. We’ll use an open dataset consisting of full fund holdings graciously provided by Morningstar. My goal in presenting this use case are to have the audience learn about how these technologies can be applied to a real world problem and to inspire members of the audience to start learning these technologies and applying them to their own projects.

Spark, Python and Parquet

Spark, Python and Parquet

Spark, Python and Parquet

Create and operationalize a predictive model using Microsoft Azure Machine Learning. – Perform the typical steps involved in building a predictive analytics solution such as data ingestion, data cleansing, data exploration, feature engineering, model selection and evaluation of model results –learn how to use machine learning with big data scenarios using tools like Hadoop and SQL Server to process and work with such data.

Building a Predictive Analytics Solution with Azure ML

Building a Predictive Analytics Solution with Azure ML

Building a Predictive Analytics Solution with Azure ML

Finding and classifying the mentions of the things named in text, often called Named Entity Recognition or NER, is a fundamental task in many search and analysis applications. Mature, robust NER technology is available for many languages and domains, from people, places, and products, to diseases, genes, and molecules. However, for emerging tasks like knowledge-base construction, mentions alone are insufficient. In this presentation we’ll explore techniques that go beyond names to: link mentions to one another and to rich knowledge sources like Wikidata discover and characterise the relationships between entities that are explicit in the text And we’ll discuss some of the most important practical implications of these advancements for open data science.

Beyond Names

According to Credit Suisse’s Gender 3000 report, at the end of 2013, women accounted for 12.9% of top management in 3000 companies across 40 countries. However, since 2009, companies with women as 25-50% of their management team returned 22-29%. If companies with women in management outperform so dramatically, what would happen if you invested in women-led companies? Karen Rubin will explore this question and share her findings after running a 12 year investment simulation.

How Woman are Conquering the S&P 500

How Woman are Conquering the S&P 500

How Woman are Conquering the S&P 500

Data science allows us to turn a dark forest into a world of perpetual twilight by giving us the tools to better understand the data that surrounds us. Unfortunately, in this world of twilight we still need a flashlight to get a clean crisp image of our immediate surroundings. We will talk about how to use deep domain expertise as that flashlight shedding light on our understanding of data. Our focus will be on using text analysis as a means to examine qualitative information in a structured, quantitative way. We will draw heavily from examples in complex central bank policy and financial regulation.

Domain Expertise and Unstructured Data

Domain Expertise and Unstructured Data

Domain Expertise and Unstructured Data

Kaggle The Home of Data Science

Kaggle The Home of Data Science

Kaggle The Home of Data Science

This talk shares the presenter’s experience with open source tools in data science competitions. In the past several years Kaggle and other competitions have created a large online community of data scientists. In addition to competing with each other for fame and glory, members of this community also generously share knowledge, insights using forum and open source code. The open competition and sharing have resulted in rapid progress in the sophistication of the entire community. This presentation will briefly cover this journey from a competitor’s perspective, and share hands on tips on some open source tools proven popular and useful in recent competitions.

Open Source Tools & Data Science Competitions

Open Source Tools & Data Science Competitions

Open Source Tools & Data Science Competitions

scikit-learn has emerged as one of the most popular open source machine learning toolkits, now widely used in academia and industry. scikit-learn provides easy-to-use interfaces to perform advanced analysis and build powerful predictive models. The tutorial will cover basic concepts of machine learning, such as supervised and unsupervised learning, cross validation, and model selection. We will see how to prepare data for machine learning, and go from applying a single algorithm to building a machine learning pipeline. We will also cover how to build machine learning models on text data, and how to handle very large datasets.

Machine Learning with scikit-learn

Machine Learning with scikit-learn

Machine Learning with scikit-learn

Despite the proliferation of open-source tools for analysis (such as Python and R) and those used for visualization (such as Javascript / D3), there often exist significant gaps between these areas, and those of us trying to navigate the complete arc from data to insight can encounter many obstacles along the way. Fortunately, in recent years there have been many efforts to fill these needs, and today distilling a meaningful visualization from raw data is faster and easier than ever before. In this talk we will use will use examples in geospatial analysis and visualization to illustrate how to open-source tools like Python, geopandas, and TileMill work together. Using examples from the RunKeeper mobile app we will show how we currently use these tools to understand better our customers and their data, and to communicate with our colleagues, external partners, and the data community at large.

Bridging the Gap Between Data and Insight using Open-Source Tools

Bridging the Gap Between Data and Insight using Open-Source Tools

Bridging the Gap Between Data and Insight using Open-Source Tools

Top 10 Signs of the Textpocalypse

Top 10 Signs of the Textpocalypse

Top 10 Signs of the Textpocalypse

The Art of Data Science

The Art of Data Science

The Art of Data Science

Frontiers of Open Data Science Research

Frontiers of Open Data Science Research

Frontiers of Open Data Science Research

One of the most important, yet often overlooked, aspects of predictive modeling is the transformation of data to create model inputs, better known as feature engineering (FE). This talk will go into the theoretical background behind FE, showing how it leverages existing data to produce better modeling results. It will then detail some important FE techniques that should be in every data scientist’s tool kit.

Feature Engineering

Feature Engineering

Feature Engineering

To rephrase an old saying: ‘It takes a village to raise an Analyst.’ Data Analysts and Scientists are working in teams delivering insight and analysis on an ongoing basis. So how do you get the team to support experimentation and insight delivery without ending up in an IT Engineer vs Analyst vs Data Governance war? We present 5 shocking steps to get these teams of people working together with practical, doable steps that can help you achieve data agility. The speaker has decades of hands on and executive management experience in data, analytics, and software development.

Agile Data

Just like every major corporation today, nonprofits and governments have more data than ever before. And just like those corporations, they are eager to tap into the power of their data. But the social sector doesn’t have the same resources to attract talent. Jeff Hammerbacher, Chief Scientist at Cloudera, put it best: “The best minds of my generation are thinking about how to make people click ads. That sucks.” At DrivenData our goal is to make the world suck a little less by empowering impact organizations to get the most from their data. Peter Bull, co-founder at DrivenData, will speak on the ways in which statistics, computer science, and machine learning can be applied to the challenges in the social sector. The talk will address both the big-picture context of the data for good movement, and an in-depth case study of the methods which won DrivenData’s recent machine learning competitions. It’s an exciting time for people who love data: methods are improving, computational costs are decreasing, storage and transport are cheaper, and the talent pool is growing. It’s up to the data geeks to use these powers for good.

Using your powers for good: Data science in the social sector

Using your powers for good: Data science in the social sector

Using your powers for good: Data science in the social sector

You will learn the basic concepts of machine learning – such as Modeling, Model Selection, Loss or Profit, overfitting, and validation – in a non-mathematical way, so that you can ask for data analysis and interpret the results of a model in the context of making business decisions. The concepts behind machine learning are actually quite simple, so expect to take away not just words and acronyms, but rather, a deep understanding. We will work in the context of concrete examples from different domains, including finance and medicine. What is probability? What is a model? Supervised vs unsupervised learning. Regression and Classification. Models and Data: Bias, Variance, Noise, Overfitting, and how to solve Overfitting with Regularization and Validation Risk and Cost, Data snooping, asymmetry in data, experiments. How good is a model? Profit Curves, ROC curves, and the expected value formalism.

Machine Learning for Suits

Machine Learning for Suits

Machine Learning for Suits

Recurrent Neural Networks hold great promise as general sequence learning algorithms. As such, they are a very promising tool for text analysis. However, outside of very specific use cases such as handwriting recognition and recently, machine translation, they have not seen wide spread use. Why has this been the case? In this presentation, we will first introduce RNNs as a concept. Then we will sketch how to implement them and cover the tricks necessary to make them work well. With the basics covered, we will investigate using RNNs as general text classification and regression models, examining where they succeed and where they fail compared to more traditional text analysis models. A straightforward open-source Python and Theano library for training RNNs with a scikit-learn style interface will be introduced and we’ll see how to use it through a tutorial on a real world text dataset

Recurrent Neural Networks for Text Analysis

Recurrent Neural Networks for Text Analysis

Recurrent Neural Networks for Text Analysis

The workshop is an overview of creating predictive models using R. An example data set will be used to demonstrate a typical workflow: data splitting, pre-processing, model tuning and evaluation. Several R packages will be shown along with the caret package which provides a unified interface to a large number of R’s modeling functions and enables parallel processing. Participants should have a basic understanding of R data structures and basic language elements (i.e. functions, classes, etc).

Predictive Modeling Workshop

Predictive Modeling Workshop

Predictive Modeling Workshop

From social networks to protein networks to financial transactions, graphs are everywhere. Graph Analytics represent a key tool for data science to take advance of this type of network information. Many “Bigdata” and NoSQL techniques for analysis and data science that work well for relational and structured data, do not scale effectively when applied to challenges in graph analytics and traversal algorithms. The data locality and graph access patterns challenge existing HW architectures and place a premium on bandwidth to main memory.GPUs currently have 10X advantage over CPUs in this area. The advantage is projected to grow to 100X by 2016. This talk will discuss why GPUs are game-changer by dramatically improving the price-performance ratio for very large graph analytics over existing technologies. It will present results for work in GPU Acceleration of graph analytics within both research and industry applications.

Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of D...

Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of D...

Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of D...

Can We Automate Predictive Analytics

Can We Automate Predictive Analytics

Can We Automate Predictive Analytics

More from odsc (20)

Spark, Python and Parquet

Spark, Python and Parquet

Spark, Python and Parquet

Building a Predictive Analytics Solution with Azure ML

Building a Predictive Analytics Solution with Azure ML

Building a Predictive Analytics Solution with Azure ML

Beyond Names

How Woman are Conquering the S&P 500

How Woman are Conquering the S&P 500

How Woman are Conquering the S&P 500

Domain Expertise and Unstructured Data

Domain Expertise and Unstructured Data

Domain Expertise and Unstructured Data

Kaggle The Home of Data Science

Kaggle The Home of Data Science

Kaggle The Home of Data Science

Open Source Tools & Data Science Competitions

Open Source Tools & Data Science Competitions

Open Source Tools & Data Science Competitions

Machine Learning with scikit-learn

Machine Learning with scikit-learn

Machine Learning with scikit-learn

Bridging the Gap Between Data and Insight using Open-Source Tools

Bridging the Gap Between Data and Insight using Open-Source Tools

Bridging the Gap Between Data and Insight using Open-Source Tools

Top 10 Signs of the Textpocalypse

Top 10 Signs of the Textpocalypse

Top 10 Signs of the Textpocalypse

The Art of Data Science

The Art of Data Science

The Art of Data Science

Frontiers of Open Data Science Research

Frontiers of Open Data Science Research

Frontiers of Open Data Science Research

Feature Engineering

Feature Engineering

Feature Engineering

Agile Data

Using your powers for good: Data science in the social sector

Using your powers for good: Data science in the social sector

Using your powers for good: Data science in the social sector

Machine Learning for Suits

Machine Learning for Suits

Machine Learning for Suits

Recurrent Neural Networks for Text Analysis

Recurrent Neural Networks for Text Analysis

Recurrent Neural Networks for Text Analysis

Predictive Modeling Workshop

Predictive Modeling Workshop

Predictive Modeling Workshop

Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of D...

Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of D...

Enabling Graph Analytics at Scale: The Opportunity for GPU-Acceleration of D...

Can We Automate Predictive Analytics

Can We Automate Predictive Analytics

Can We Automate Predictive Analytics

Recently uploaded

Automating Google Workspace (GWS) & more with Apps Script

Automating Google Workspace (GWS) & more with Apps Script

Automating Google Workspace (GWS) & more with Apps Script

BooK Now Call us at +918448380779 to hire a gorgeous and seductive call girl for sex. Take a Delhi Escort Service. The help of our escort agency is mostly meant for men who want sexual Indian Escorts In Delhi NCR. It should be noted that any impersonator will get 100 attention from our Young Girls Escorts in Delhi. They will assume the position of reliable allies. VIP Call Girl With Original Photos Book Tonight +918448380779 Our Cheap Price 1 Hour not available 2 Hours 5000 Full Night 8000 TAG: Call Girls in Delhi, Noida, Gurgaon, Ghaziabad, Connaught Place, Greater Kailash Delhi, Lajpat Nagar Delhi, Mayur Vihar Delhi, Chanakyapuri Delhi, New Friends Colony Delhi, Majnu Ka Tilla, Karol Bagh, Malviya Nagar, Saket, Khan Market, Noida Sector 18, Noida Sector 76, Noida Sector 51, Gurgaon Mg Road, Iffco Chowk Gurgaon, Rajiv Chowk Gurgaon All Delhi Ncr Free Home Deliver

08448380779 Call Girls In Friends Colony Women Seeking Men

08448380779 Call Girls In Friends Colony Women Seeking Men

08448380779 Call Girls In Friends Colony Women Seeking Men

Delhi Call girls

Evaluating the top large language models.pdf

Evaluating the top large language models.pdf

Evaluating the top large language models.pdf

ChristopherTHyatt

🐬 The future of MySQL is Postgres 🐘

🐬 The future of MySQL is Postgres 🐘

🐬 The future of MySQL is Postgres 🐘

Discord is a free app offering voice, video, and text chat functionalities, primarily catering to the gaming community. It serves as a hub for users to create and join servers tailored to their interests. Discord’s ecosystem comprises servers, each functioning as a distinct online community with its own channels dedicated to specific topics or activities. Users can engage in text-based discussions, voice calls, or video chats within these channels. Understanding Discord Servers Discord servers are virtual spaces where users congregate to interact, share content, and build communities. Servers may revolve around gaming, hobbies, interests, or fandoms, providing a platform for like-minded individuals to connect. Communication Features Discord offers a range of communication tools, including text channels for messaging, voice channels for real-time audio conversations, and video channels for face-to-face interactions. These features facilitate seamless communication and collaboration. What Does NSFW Mean? The acronym NSFW stands for “Not Safe For Work,” indicating content that may be inappropriate for professional or public settings. NSFW Content NSFW content encompasses material that is sexually explicit, violent, or otherwise graphic in nature. It often includes nudity, profanity, or depictions of sensitive topics.

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

What are drone anti-jamming systems? The drone anti-jamming systems and anti-spoof technology protect against interference, jamming, and spoofing of the UAVs. To protect their security, countries are beginning to research drone anti-jamming systems, also known as drone strike weapons. The anti-jam and anti-spoof technology protects against interference, jamming and spoofing. A drone strike weapon is a drone attack weapon that can attack and destroy enemy drones. So what is so unique about this amazing system?

What Are The Drone Anti-jamming Systems Technology?

What Are The Drone Anti-jamming Systems Technology?

What Are The Drone Anti-jamming Systems Technology?

Antenna Manufacturer Coco

[2024]Digital Global Overview Report 2024 Meltwater.pdf

[2024]Digital Global Overview Report 2024 Meltwater.pdf

[2024]Digital Global Overview Report 2024 Meltwater.pdf

Tech Trends Report 2024 Future Today Institute.pdf

Tech Trends Report 2024 Future Today Institute.pdf

Tech Trends Report 2024 Future Today Institute.pdf

GenCyber Cyber Security Day Presentation

GenCyber Cyber Security Day Presentation

GenCyber Cyber Security Day Presentation

Michael W. Hawkins

CNv6 Instructor Chapter 6 Quality of Service

CNv6 Instructor Chapter 6 Quality of Service

CNv6 Instructor Chapter 6 Quality of Service

Enterprise Knowledge’s Urmi Majumder, Principal Data Architecture Consultant, and Fernando Aguilar Islas, Senior Data Science Consultant, presented "Driving Behavioral Change for Information Management through Data-Driven Green Strategy" on March 27, 2024 at Enterprise Data World (EDW) in Orlando, Florida. In this presentation, Urmi and Fernando discussed a case study describing how the information management division in a large supply chain organization drove user behavior change through awareness of the carbon footprint of their duplicated and near-duplicated content, identified via advanced data analytics. Check out their presentation to gain valuable perspectives on utilizing data-driven strategies to influence positive behavioral shifts and support sustainability initiatives within your organization. In this session, participants gained answers to the following questions: - What is a Green Information Management (IM) Strategy, and why should you have one? - How can Artificial Intelligence (AI) and Machine Learning (ML) support your Green IM Strategy through content deduplication? - How can an organization use insights into their data to influence employee behavior for IM? - How can you reap additional benefits from content reduction that go beyond Green IM?

Driving Behavioral Change for Information Management through Data-Driven Gree...

Driving Behavioral Change for Information Management through Data-Driven Gree...

Driving Behavioral Change for Information Management through Data-Driven Gree...

Enterprise Knowledge

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

The Digital Insurer

What is a good lead in your organisation? Which leads are priority? What happens to leads? When sales and marketing give different answers to these questions, or perhaps aren't sure of the answers at all, frustrations build and opportunities are left on the table. Join us for an illuminating session with Cian McLoughlin, HubSpot Principal Customer Success Manager, as we look at that crucial piece of the customer journey in which leads are transferred from marketing to sales.

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

sudhanshuwaghmare1

In an era where artificial intelligence (AI) stands at the forefront of business innovation, Information Architecture (IA) is at the core of functionality. See “There’s No AI Without IA” – (from 2016 but even more relevant today) Understanding and leveraging how Information Architecture (IA) supports AI synergies between knowledge engineering and prompt engineering is critical for senior leaders looking to successfully deploy AI for internal and externally facing knowledge processes. This webinar be a high-level overview of the methodologies that can elevate AI-driven knowledge processes supporting both employees and customers. Core Insights Include: Strategic Knowledge Engineering: Delve into how structuring AI's knowledge base is required to prevent hallucinations, enable contextual retrieval of accurate information. This will include discussion of gold standard libraries of use cases support testing various LLMs and structures and configurations of knowledge base. Precision in Prompt Engineering: Learn the art of crafting prompts that direct AI to deliver targeted, relevant responses, thereby optimizing customer experiences and business outcomes. Unified Approach for Enhanced AI Performance: Explore the intersection of knowledge and prompt engineering to develop AI systems that are not only more responsive but also aligned with overarching business strategies. Guiding Principles for Implementation: Equip yourself with best practices, ethical guidelines, and strategic considerations for embedding these technologies into your business ecosystem effectively. This webinar is designed to empower business and technology leaders with the knowledge to harness the full potential of AI, ensuring their organizations not only keep pace with digital transformation but lead the charge. Join us to map a roadmap to fully leverage Information Architecture (IA) and AI chart a course towards a future where AI is a key pillar of strategic innovation and business success.

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx

Earley Information Science

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Product Anonymous

Data Cloud, More than a CDP by Matt Robison

Data Cloud, More than a CDP by Matt Robison

Data Cloud, More than a CDP by Matt Robison

Anna Loughnan Colquhoun

A Domino Admins Adventures (Engage 2024)

A Domino Admins Adventures (Engage 2024)

A Domino Admins Adventures (Engage 2024)

Gabriella Davis

The 7 Things I Know About Cyber Security After 25 Years | April 2024

The 7 Things I Know About Cyber Security After 25 Years | April 2024

The 7 Things I Know About Cyber Security After 25 Years | April 2024

This presentations targets students or working professionals. You may know Google for search, YouTube, Android, Chrome, and Gmail, but did you know Google has many developer tools, platforms & APIs? This comprehensive yet still high-level overview outlines the most impactful tools for where to run your code, store & analyze your data. It will also inspire you as to what's possible. This talk is 50 minutes in length.

Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

Recently uploaded (20)

Automating Google Workspace (GWS) & more with Apps Script

Automating Google Workspace (GWS) & more with Apps Script

Automating Google Workspace (GWS) & more with Apps Script

08448380779 Call Girls In Friends Colony Women Seeking Men

08448380779 Call Girls In Friends Colony Women Seeking Men

08448380779 Call Girls In Friends Colony Women Seeking Men

Evaluating the top large language models.pdf

Evaluating the top large language models.pdf

Evaluating the top large language models.pdf

🐬 The future of MySQL is Postgres 🐘

🐬 The future of MySQL is Postgres 🐘

🐬 The future of MySQL is Postgres 🐘

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

Understanding Discord NSFW Servers A Guide for Responsible Users.pdf

What Are The Drone Anti-jamming Systems Technology?

What Are The Drone Anti-jamming Systems Technology?

What Are The Drone Anti-jamming Systems Technology?

[2024]Digital Global Overview Report 2024 Meltwater.pdf

[2024]Digital Global Overview Report 2024 Meltwater.pdf

[2024]Digital Global Overview Report 2024 Meltwater.pdf

Tech Trends Report 2024 Future Today Institute.pdf

Tech Trends Report 2024 Future Today Institute.pdf

Tech Trends Report 2024 Future Today Institute.pdf

GenCyber Cyber Security Day Presentation

GenCyber Cyber Security Day Presentation

GenCyber Cyber Security Day Presentation

CNv6 Instructor Chapter 6 Quality of Service

CNv6 Instructor Chapter 6 Quality of Service

CNv6 Instructor Chapter 6 Quality of Service

Driving Behavioral Change for Information Management through Data-Driven Gree...

Driving Behavioral Change for Information Management through Data-Driven Gree...

Driving Behavioral Change for Information Management through Data-Driven Gree...

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

04-2024-HHUG-Sales-and-Marketing-Alignment.pptx

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

Boost Fertility New Invention Ups Success Rates.pdf

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx

EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke

Data Cloud, More than a CDP by Matt Robison

Data Cloud, More than a CDP by Matt Robison

Data Cloud, More than a CDP by Matt Robison

A Domino Admins Adventures (Engage 2024)

A Domino Admins Adventures (Engage 2024)

A Domino Admins Adventures (Engage 2024)

The 7 Things I Know About Cyber Security After 25 Years | April 2024

The 7 Things I Know About Cyber Security After 25 Years | April 2024

The 7 Things I Know About Cyber Security After 25 Years | April 2024

Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

Powerful Google developer tools for immediate impact! (2023-24 C)

Data Science at Dow Jones: Monetizing Data, News and Information

1. DATA SCIENCE AT DOW JONES: MONETIZING DATA, NEWS AND INFORMATION Juan M. Huerta O P E N D A T A S C I E N C E C O N F E R E N C E_ BOSTON 2015 @opendat asci