Netflix relies on analytics to personalize content recommendations and drive subscriber engagement. It analyzes billions of daily user interactions to improve recommendations. Netflix partners with Teradata to power its analytics platform using Teradata's cloud-based data warehousing and hybrid analytical tools. This enables Netflix to gather insights, test recommendations, and focus on delivering engaging content to subscribers.
Deploy Apache Spark™ on Rackspace OnMetal™ for Cloud Big Data PlatformRackspace
There's an elephant in the room when it comes to Big Data. Apache Hadoop and Spark offer the promise to transform how businesses leverage Big Data, finding the right mix of flexible deployments, elastic scalability, and performance can be daunting.
Introducing Rackspace OnMetal™ for Apache Spark™ an industry first that combines the performance and efficiency of bare metal with the ease and flexibility of cloud. With Rackspace OnMetal for Cloud Big Data Platform you can transform how you run Hadoop and Spark workloads:
•Deploy in minutes, not months
•Spin instances up or down on demand
•Process data in-memory for faster query times
•Get bare metal performance and say goodbye to virtualization taxes
Sign up and learn how Rackspace OnMetal for Cloud Big Data Platform can rapidly move your organization from planning to deploying.
Netflix - Elevating Your Data Platform - TDWI Keynote - San Diego 2015Kurt Brown
Are you getting the most out of your data platform? The technologies you choose are important, but even more so is how you put them into practice. Part philosophy and part pragmatic reality, I'll dive into our thinking at Netflix on technology selection and trade-offs, challenging everything (constructively), providing building blocks and paved paths, staffing, and more. I'll also talk through our tech stack, which includes many big data technologies (e.g. Hadoop, Spark, and Presto), traditional BI tools (e.g. Teradata, MicroStrategy, and Tableau), and custom tools / services (e.g. our big data portal and API). My hope (and expectation!) is that you'll leave with an arsenal of new ideas on the best way to get things done.
DataOps for the Modern Data Warehouse on Microsoft Azure @ NDCOslo 2020 - Lac...Lace Lofranco
Talk Description:
The Modern Data Warehouse architecture is a response to the emergence of Big Data, Machine Learning and Advanced Analytics. DevOps is a key aspect of successfully operationalising a multi-source Modern Data Warehouse.
While there are many examples of how to build CI/CD pipelines for traditional applications, applying these concepts to Big Data Analytical Pipelines is a relatively new and emerging area. In this demo heavy session, we will see how to apply DevOps principles to an end-to-end Data Pipeline built on the Microsoft Azure Data Platform with technologies such as Data Factory, Databricks, Data Lake Gen2, Azure Synapse, and AzureDevOps.
Resources: https://aka.ms/mdw-dataops
From weeks to hours big data analytics with tableau and amazon web services ...Amazon Web Services
Amazon Web Services and Tableau Software have shifted how organizations store and access their data. The fast, scalable, and cost efficient services that Amazon Web Services provides for housing data combined with Tableau's visual analytics solution means that within hours an organization can securely put the power of their massive data assets into the hands of their domain experts removing expensive overhead and lengthy setup-up time. Go from a petabyte scale data warehouse setup to leveraging visual analytics in just a couple of hours. Learn how leaders in managing big data are taking advantage of disruptive technology.
In this presentation you'll learn how to:
Empower visual data discovery against big data via a live demo of AWS and Tableau working together
Revolutionize corporate reporting and dashboards, including examples of customer case studies.
Promote data driven decision making at every level
Speaker: Jason Oakes, Sales Consultant, Tableau
Deploy Apache Spark™ on Rackspace OnMetal™ for Cloud Big Data PlatformRackspace
There's an elephant in the room when it comes to Big Data. Apache Hadoop and Spark offer the promise to transform how businesses leverage Big Data, finding the right mix of flexible deployments, elastic scalability, and performance can be daunting.
Introducing Rackspace OnMetal™ for Apache Spark™ an industry first that combines the performance and efficiency of bare metal with the ease and flexibility of cloud. With Rackspace OnMetal for Cloud Big Data Platform you can transform how you run Hadoop and Spark workloads:
•Deploy in minutes, not months
•Spin instances up or down on demand
•Process data in-memory for faster query times
•Get bare metal performance and say goodbye to virtualization taxes
Sign up and learn how Rackspace OnMetal for Cloud Big Data Platform can rapidly move your organization from planning to deploying.
Netflix - Elevating Your Data Platform - TDWI Keynote - San Diego 2015Kurt Brown
Are you getting the most out of your data platform? The technologies you choose are important, but even more so is how you put them into practice. Part philosophy and part pragmatic reality, I'll dive into our thinking at Netflix on technology selection and trade-offs, challenging everything (constructively), providing building blocks and paved paths, staffing, and more. I'll also talk through our tech stack, which includes many big data technologies (e.g. Hadoop, Spark, and Presto), traditional BI tools (e.g. Teradata, MicroStrategy, and Tableau), and custom tools / services (e.g. our big data portal and API). My hope (and expectation!) is that you'll leave with an arsenal of new ideas on the best way to get things done.
DataOps for the Modern Data Warehouse on Microsoft Azure @ NDCOslo 2020 - Lac...Lace Lofranco
Talk Description:
The Modern Data Warehouse architecture is a response to the emergence of Big Data, Machine Learning and Advanced Analytics. DevOps is a key aspect of successfully operationalising a multi-source Modern Data Warehouse.
While there are many examples of how to build CI/CD pipelines for traditional applications, applying these concepts to Big Data Analytical Pipelines is a relatively new and emerging area. In this demo heavy session, we will see how to apply DevOps principles to an end-to-end Data Pipeline built on the Microsoft Azure Data Platform with technologies such as Data Factory, Databricks, Data Lake Gen2, Azure Synapse, and AzureDevOps.
Resources: https://aka.ms/mdw-dataops
From weeks to hours big data analytics with tableau and amazon web services ...Amazon Web Services
Amazon Web Services and Tableau Software have shifted how organizations store and access their data. The fast, scalable, and cost efficient services that Amazon Web Services provides for housing data combined with Tableau's visual analytics solution means that within hours an organization can securely put the power of their massive data assets into the hands of their domain experts removing expensive overhead and lengthy setup-up time. Go from a petabyte scale data warehouse setup to leveraging visual analytics in just a couple of hours. Learn how leaders in managing big data are taking advantage of disruptive technology.
In this presentation you'll learn how to:
Empower visual data discovery against big data via a live demo of AWS and Tableau working together
Revolutionize corporate reporting and dashboards, including examples of customer case studies.
Promote data driven decision making at every level
Speaker: Jason Oakes, Sales Consultant, Tableau
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Transforming Devon’s Data Pipeline with an Open Source Data Hub—Built on Data...Databricks
How did Devon move from a traditional reporting and data warehouse approach to a modern data lake? What did it take to go from a slow and brittle technical landscape to an a flexible, scalable, and agile platform? In the past, Devon addressed data solutions in dozens of ways depending on the user and the requirements. Through a visionary program, driven by Databricks, Devon has begun a transformation of how it consumes data and enables engineers, analysts, and IT developers to deliver data driven solutions along all levels of the data analytics spectrum. We will share the vision, technical architecture, influential decisions, and lessons learned from our journey. Join us to hear the unique Databricks success story at Devon.
This is the complete deck presented at the Westin Calgary Hotel, on August 16th, 2016.
It covers the current state of the AWS Big Data Solution set. Contains several use cases of Big Data, Machine Learning, and a tutorial on how to implement and use Big Data on the AWS Cloud Platform.
AWS Cloud Kata 2013 | Singapore - Getting to Scale on AWSAmazon Web Services
This session will focus on how to get from 'Minimum Viable Product' (MVP) to scale. It will also explain how to deal with unpredictable demand and how to build a scalable business. Attend this session to learn how to:
Scale web servers and app services with Elastic Load Balancing and Auto Scaling on Amazon EC2
Scale your storage on Amazon S3 and S3 Reduced Redundancy Storage
Scale your database with Amazon DynamoDB, Amazon RDS, and Amazon ElastiCache
Scale your customer base by reaching customers globally in minutes with Amazon CloudFront
Slides from Michelle Ufford's talk, Data-Driven @ Netflix. Talk given at PASS Summit 2016 in October 2016.
Netflix is the quintessential data-driven company. It’s 83 million members stream more than 125 million hours in over 190 countries every day and generate more than 700 billion events in the process. In this session, we’ll share how data is used to make informed decisions across the entire business — from content acquisition to content delivery, and everything in between. We’ll look at how Netflix successfully employs a scalable cloud-based data platform to support a constant deluge of data and a small army of data analysts, engineers, and scientists. We’ll discuss the advanced analytical capabilities that are enabled through modern data technologies. Lastly, we’ll explore some of the architectural & operational principals that enable Netflix to so effectively make use of its data.
Expert IT analyst groups like Wikibon forecast that NoSQL database usage will grow at a compound rate of 60% each year for the next five years, and Gartner Groups says NoSQL databases are one of the top trends impacting information management in 2013. But is NoSQL right for your business? How do you know which business applications will benefit from NoSQL and which won't? What questions do you need to ask in order to make such decisions?
If you're wondering what NoSQL is and if your business can benefit from NoSQL technology, join DataStax for the Webinar, "How to Tell if Your Business Needs NoSQL". This to-the-point presentation will provide practical litmus tests to help you understand whether NoSQL is right for your use case, and supplies examples of NoSQL technology in action with leading businesses that demonstrate how and where NoSQL databases can have the greatest impact."
Speaker: Robin Schumacher, Vice President of Products at DataStax
Robin Schumacher has spent the last 20 years working with databases and big data. He comes to DataStax from EnterpriseDB, where he built and led a market-driven product management group. Previously, Robin started and led the product management team at MySQL for three years before they were bought by Sun (the largest open source acquisition in history), and then by Oracle. He also started and led the product management team at Embarcadero Technologies, which was the #1 IPO in 2000. Robin is the author of three database performance books and frequent speaker at industry events. Robin holds BS, MA, and Ph.D. degrees from various universities.
Learn more about Talend Integration Cloud - http://www.talend.com/products/integration-cloud
Talend Integration Cloud includes the powerful Talend Studio and new web-based designer tools to maximize your productivity. Speed cloud integration using robust graphical tools and wizards inside Talend Integration Cloud. More than 900 connectors and components simplify development of cloud-to-cloud and hybrid integration flows to deploy as governed integration services. Build simple or complex integration flows inside Talend Studio that connect, cleanse, and transform data. Simply push a button to publish and go live in seconds. Easily de-duplicate and standardize data to increase information accuracy and completeness.
Webinar: BI in the Sky - The New Rules of Cloud AnalyticsSnapLogic
In this webinar, we talk about the shift in data gravity as more and more business applications are moving to the cloud, and how the ability to deliver analytics in the cloud has evolved from idea to enterprise reality with new solutions being announced constantly that appeal to the need for speed, simplicity and access to insight on demand. Joining us in this webinar is David Glueck, Sr. Director of Data Science and Engineering at Bonobos.
To learn more, visit: www.SnapLogic.com/salesforce-analytics
Webinar with SnagAJob, HP Vertica and Looker - Data at the speed of busines s...Looker
Enterprise companies are struggling to manage increasing demands for data with legacy BI tools. By centralizing their data in Vertica, SnagAJob, an online marketplace for hourly jobs with over 60 million users, can now use Looker to create a single source of truth and put data in the hands of decision-makers across the company.
The breath and depth of Azure products that fall under the AI and ML umbrella can be difficult to follow. In this presentation I’ll first define exactly what AI, ML, and deep learning is, and then go over the various Microsoft AI and ML products and their use cases.
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
A modern data warehouse lets you bring together all your data at any scale easily, and to get insights through analytical dashboards, operational reports, or advanced analytics for all your users.
Azure Synapse Analytics is Azure SQL Data Warehouse evolved: a limitless analytics service, that brings together enterprise data warehousing and Big Data analytics into a single service. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources, at scale. Azure Synapse brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate business intelligence and machine learning needs. This is a huge deck with lots of screenshots so you can see exactly how it works.
Transforming Devon’s Data Pipeline with an Open Source Data Hub—Built on Data...Databricks
How did Devon move from a traditional reporting and data warehouse approach to a modern data lake? What did it take to go from a slow and brittle technical landscape to an a flexible, scalable, and agile platform? In the past, Devon addressed data solutions in dozens of ways depending on the user and the requirements. Through a visionary program, driven by Databricks, Devon has begun a transformation of how it consumes data and enables engineers, analysts, and IT developers to deliver data driven solutions along all levels of the data analytics spectrum. We will share the vision, technical architecture, influential decisions, and lessons learned from our journey. Join us to hear the unique Databricks success story at Devon.
This is the complete deck presented at the Westin Calgary Hotel, on August 16th, 2016.
It covers the current state of the AWS Big Data Solution set. Contains several use cases of Big Data, Machine Learning, and a tutorial on how to implement and use Big Data on the AWS Cloud Platform.
AWS Cloud Kata 2013 | Singapore - Getting to Scale on AWSAmazon Web Services
This session will focus on how to get from 'Minimum Viable Product' (MVP) to scale. It will also explain how to deal with unpredictable demand and how to build a scalable business. Attend this session to learn how to:
Scale web servers and app services with Elastic Load Balancing and Auto Scaling on Amazon EC2
Scale your storage on Amazon S3 and S3 Reduced Redundancy Storage
Scale your database with Amazon DynamoDB, Amazon RDS, and Amazon ElastiCache
Scale your customer base by reaching customers globally in minutes with Amazon CloudFront
Slides from Michelle Ufford's talk, Data-Driven @ Netflix. Talk given at PASS Summit 2016 in October 2016.
Netflix is the quintessential data-driven company. It’s 83 million members stream more than 125 million hours in over 190 countries every day and generate more than 700 billion events in the process. In this session, we’ll share how data is used to make informed decisions across the entire business — from content acquisition to content delivery, and everything in between. We’ll look at how Netflix successfully employs a scalable cloud-based data platform to support a constant deluge of data and a small army of data analysts, engineers, and scientists. We’ll discuss the advanced analytical capabilities that are enabled through modern data technologies. Lastly, we’ll explore some of the architectural & operational principals that enable Netflix to so effectively make use of its data.
Expert IT analyst groups like Wikibon forecast that NoSQL database usage will grow at a compound rate of 60% each year for the next five years, and Gartner Groups says NoSQL databases are one of the top trends impacting information management in 2013. But is NoSQL right for your business? How do you know which business applications will benefit from NoSQL and which won't? What questions do you need to ask in order to make such decisions?
If you're wondering what NoSQL is and if your business can benefit from NoSQL technology, join DataStax for the Webinar, "How to Tell if Your Business Needs NoSQL". This to-the-point presentation will provide practical litmus tests to help you understand whether NoSQL is right for your use case, and supplies examples of NoSQL technology in action with leading businesses that demonstrate how and where NoSQL databases can have the greatest impact."
Speaker: Robin Schumacher, Vice President of Products at DataStax
Robin Schumacher has spent the last 20 years working with databases and big data. He comes to DataStax from EnterpriseDB, where he built and led a market-driven product management group. Previously, Robin started and led the product management team at MySQL for three years before they were bought by Sun (the largest open source acquisition in history), and then by Oracle. He also started and led the product management team at Embarcadero Technologies, which was the #1 IPO in 2000. Robin is the author of three database performance books and frequent speaker at industry events. Robin holds BS, MA, and Ph.D. degrees from various universities.
Learn more about Talend Integration Cloud - http://www.talend.com/products/integration-cloud
Talend Integration Cloud includes the powerful Talend Studio and new web-based designer tools to maximize your productivity. Speed cloud integration using robust graphical tools and wizards inside Talend Integration Cloud. More than 900 connectors and components simplify development of cloud-to-cloud and hybrid integration flows to deploy as governed integration services. Build simple or complex integration flows inside Talend Studio that connect, cleanse, and transform data. Simply push a button to publish and go live in seconds. Easily de-duplicate and standardize data to increase information accuracy and completeness.
Webinar: BI in the Sky - The New Rules of Cloud AnalyticsSnapLogic
In this webinar, we talk about the shift in data gravity as more and more business applications are moving to the cloud, and how the ability to deliver analytics in the cloud has evolved from idea to enterprise reality with new solutions being announced constantly that appeal to the need for speed, simplicity and access to insight on demand. Joining us in this webinar is David Glueck, Sr. Director of Data Science and Engineering at Bonobos.
To learn more, visit: www.SnapLogic.com/salesforce-analytics
Webinar with SnagAJob, HP Vertica and Looker - Data at the speed of busines s...Looker
Enterprise companies are struggling to manage increasing demands for data with legacy BI tools. By centralizing their data in Vertica, SnagAJob, an online marketplace for hourly jobs with over 60 million users, can now use Looker to create a single source of truth and put data in the hands of decision-makers across the company.
The breath and depth of Azure products that fall under the AI and ML umbrella can be difficult to follow. In this presentation I’ll first define exactly what AI, ML, and deep learning is, and then go over the various Microsoft AI and ML products and their use cases.
Cortana Analytics Workshop: The "Big Data" of the Cortana Analytics Suite, Pa...MSAdvAnalytics
Lance Olson. Cortana Analytics is a fully managed big data and advanced analytics suite that helps you transform your data into intelligent action. Come to this two-part session to learn how you can do "big data" processing and storage in Cortana Analytics. In the first part, we will provide an overview of the processing and storage services. We will then talk about the patterns and use cases which make up most big data solutions. In the second part, we will go hands-on, showing you how to get started today with writing batch/interactive queries, real-time stream processing, or NoSQL transactions all over the same repository of data. Crunch petabytes of data by scaling out your computation power to any sized cluster. Store any amount of unstructured data in its native format with no limits to file or account size. All of this can be done with no hardware to acquire or maintain and minimal time to setup giving you the value of "big data" within minutes. Go to https://channel9.msdn.com/ to find the recording of this session.
A modern data warehouse lets you bring together all your data at any scale easily, and to get insights through analytical dashboards, operational reports, or advanced analytics for all your users.
Gartner says that for CEOs, “Growth is the top priority, by far. In 2014, it almost equals the sum of the next three top issues”. Companies effectively using software development to achieve competitive advantage are more profitable than their peers. Organizations such as Square, Uber, Netflix, Airbnb, the Climate Corporation and Etsy are using software to change industries and disrupt business models. Put another way, software is eating the world. Companies looking to drive innovation through software development have new options and opportunities.
Data Virtualization, a Strategic IT Investment to Build Modern Enterprise Dat...Denodo
This content was presented during the Smart Data Summit Dubai 2015 in the UAE on May 25, 2015, by Jesus Barrasa, Senior Solutions Architect at Denodo Technologies.
In the era of Big Data, IoT, Cloud and Social Media, Information Architects are forced to rethink how to tackle data management and integration in the enterprise. Traditional approaches based on data replication and rigid information models lack the flexibility to deal with this new hybrid reality. New data sources and an increasing variety of consuming applications, like mobile apps and SaaS, add more complexity to the problem of delivering the right data, in the right format, and at the right time to the business. Data Virtualization emerges in this new scenario as the key enabler of agile, maintainable and future-proof data architectures.
Semantic 'Radar' Steers Users to Insights in the Data LakeCognizant
By infusing information with intelligence, users can discover meaning in the digital data that envelops people, organizations, processes, products and things.
Big Data Everywhere Chicago: Platfora - Practices for Customer Analytics on H...BigDataEverywhere
Hadoop use cases have historically trended towards cost reduction through data warehouse offload. More recently, an uptick around customer-centric use cases have proven the ability for Hadoop to drive top-line revenue. In this session, Platfora solution architect Rob Rosen will discuss how the ability to coreelate multi-structured data in Hadoop leads to greater customer adoption, expanded cross-selling and reduced customer churn for enterprises deploying Hadoop-centric data lakes.
100 day plan - Technology Vision Australian Perspectiveaccenture
Put this 100-day plan into action to gain a deeper understanding of who your core users are and identify opportunities to better serve individual needs.
Softchoice is helping companies reach their goals of having a modern, enabling IT organization. We help customers by enabling end users, enabling hybrid IT, enabling asset management and enabling procurement.
Now companies are in the middle of a renovation that forces them to be analytics-driven to
continue being competitive. Data analysis provides a complete insight about their business. It
also gives noteworthy advantages over their competitors. Analytics-driven insights compel
businesses to take action on service innovation, enhance client experience, detect irregularities in
process and provide extra time for product or service marketing. To work on analytics driven
activities, companies require to gather, analyse and store information from all possible sources.
Companies should bring appropriate tools and workflows in practice to analyse data rapidly and
unceasingly. They should obtain insight from data analysis result and make changes in their
business process and practice on the basis of gained result. It would help to be more agile than
their previous process and function.
Semantic 'Radar' Steers Users to Insights in the Data LakeThomas Kelly, PMP
By infusing information with intelligence, users can discover meaning in the digital data that envelops people, organizations, processes, products and things.
In simple words, DataOps is all about aligning the way you manage your data with the objectives you have for that data. Let’s know in detail what actually DataOps is!
In a hyper-connected world, the agile data center helps grow the business by delivering the right services to users in a scalable, flexible and secure.
Businesses today compete at the speed of thought. Nobody can afford to stand still; if a company isn’t looking to render its best-selling products or services obsolete, somebody else will be—and that might be a known competitor or a stealthy startup.
At their best, IT departments are at the forefront of this change, enabling agile transformations of business service delivery to employees and customers. Unfortunately, while IT strives to deliver against its capabilities, too often those capabilities may be restricted because of legacy systems.
Project Deliverable 4 Analytics, Interfaces, and Cloud Technolo.docxwkyra78
Project Deliverable 4: Analytics, Interfaces, and Cloud Technology
By: Justin M. Blazejewski
CIS 499
Professor Dr. Janet Durgin
25 November 2012
Main screen
Overview | Export data | Tools | Realtime | Logout
Current month
Last
Month
Trends
c
Top selling products
Low selling products
Overview
Realtime information
Overview | Export data | Tools | Realtime | Logout
Unique ID
Activity
Result
Overview | Export data | Tools | Realtime | Logout
Reporting tools
Statistical tools
Trends
Sales 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr 8.1999999999999993 3.2 1.4 1.2 Sales 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr 8.1999999999999993 3.2 1.4 1.2 Series 1 Category 1 Category 2 Category 3 Category 4 4.3 2.5 3.5 4.5 Series 2 Category 1 Category 2 Category 3 Category 4 2.4 4.4000000000000004 1.8 2.8 Series 3 Category 1 Category 2 Category 3 Category 4 2 2 3 5 Series 1 Category 1 Category 2 Category 3 Category 4 4.3 2.5 3.5 4.5 Series 2 Category 1 Category 2 Category 3 Category 4 2.4 4.4000000000000004 1.8 2.8 Series 3 Category 1 Category 2 Category 3 Category 4 2 2 3 5
Project Deliverable 4: Analytics, Interfaces, and Cloud Technology
By: Justin M. Blazejewski
CIS 499
Professor Dr. Janet Durgin
25 November 2012
Introduction
Business Analytics means the practice of iterative and methodological examination of a business’s data with a special emphasis on statistic making. Business Analytics can further help businesses automate and optimize their business processes. Companies in which data plays a pivotal role, treats its data as a corporate assets and leverages it for gaining competitive advantage. A successful business analytics would typically depend on data quality, highly skillful and experienced professionals who understand the technologies, knows how to work with it and also understands the organizations processes in depth. Apart from this, the organization should have a capable infrastructure to support the operations of business analytics.
Usage of Business Analysis is done for the following purposes:
· Exploration of data so as to find patterns and trends
· Identifying relationships in key data variables for forecasting. For instance next probable purchase by the customer
· Drilling down to the results to find out why a particular incident took place. This approach is done by performing statistical analysis and quantitative analysis with business analytical tools
· Predicting future results by employing predictive modeling and predictive analytics
· Testing previous decisions using A/B and Multivariate testing
· Assisting business in decision making such as figuring out the amount of discount to be given for a new customer
Post identifying of business goal, an analysis methodology needs to be selected and the data is acquired to support the analysis. This data acquisition normally involves extracting data from systems that may be spread throughout different locations an ...
Similar to Netflix: Using Big Data in the Cloud to Drive Engagement (20)
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Securing your Kubernetes cluster_ a step-by-step guide to success !KatiaHIMEUR1
Today, after several years of existence, an extremely active community and an ultra-dynamic ecosystem, Kubernetes has established itself as the de facto standard in container orchestration. Thanks to a wide range of managed services, it has never been so easy to set up a ready-to-use Kubernetes cluster.
However, this ease of use means that the subject of security in Kubernetes is often left for later, or even neglected. This exposes companies to significant risks.
In this talk, I'll show you step-by-step how to secure your Kubernetes cluster for greater peace of mind and reliability.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Encryption in Microsoft 365 - ExpertsLive Netherlands 2024Albert Hoitingh
In this session I delve into the encryption technology used in Microsoft 365 and Microsoft Purview. Including the concepts of Customer Key and Double Key Encryption.
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
Netflix: Using Big Data in the Cloud to Drive Engagement
1. Netflix: Using Big Data to Drive Big Engagement
Unlocking the Power of Analytics to Drive Content and Consumer Insight
12.14 EB8564 Entertainment
2. Netflix Demonstrates Power of Analytics2 teradata.com
Non-Stop Testing and Learning Yield
Business Results
In today’s hyper-connected world, businesses are under
enormous pressure to build relationships with fully
engaged consumers who keep coming back for more.
In theory, fostering more intimate consumer relation-
ships becomes easier as new sources of data emerge,
data volumes continue their unprecedented growth, and
technology becomes more sophisticated. These develop-
ments should enable businesses to do a much better job
of personalizing marketing campaigns and generating
precise content recommendations that drive engagement,
adoption and value for subscribers.
Yet achieving an advanced understanding of one’s audi-
ence is a continuous process of testing and learning. It
demands the ability to quickly gather and reliably ana-
lyze thousands, millions, even billions of events every day
found in a variety of data sources, formats and locations—
otherwise known as Big Data. Technology platforms
crafted to gather this data and conduct the analyses must
be powerful enough to deliver timely insights today and
flexible enough to change and grow in business and tech-
nology landscapes that morph with remarkable speed.
Netflix, an undisputed leader and innovator in the over-
the-top (OTT) content space, understands this context
better than most. It has staked its business and its brand
on delivering highly targeted, personalized experiences
for every subscriber—and has even begun using its
remarkably detailed insights to change the way it buys,
licenses and develops content, causing many throughout
the Media and Entertainment industries to sit up and
take notice.
To support these efforts, Netflix leverages Teradata as
a critical component of its data and analytics platform.
More recently, the two companies partnered to transition
Netflix to the Teradata Cloud, which has given Netflix the
power and flexibility it needs—and, so, the ability to main-
tain its focus on those initiatives at the core of its business.
A Model for Data-Driven,
Consumer-Focused Business
The Netflix story is a model for data-driven,
direct-to-consumer and subscriber-based compa-
nies—and, in fact, for any business that needs engaged
audiences to thrive in a rapidly changing world.
After beginning as a mail order DVD business, Netflix
became the first prominent OTT content provider and
turned the media world on its head; witness recent deci-
sions by other major media companies to begin delivering
OTT content.
One major element in Netflix’s success is the way it relent-
lessly tweaks its recommendation engines, constantly
adapting to meet each consumer’s preferred style. Most
of the company’s streaming activity emerges from its
recommendations, which generate enormous consumer
engagement and loyalty. Every interaction a Netflix
subscriber has with the service is based on meticulously
culled and analyzed interactions—no two experiences are
the same.
In addition, as noted above, Netflix has applied its
understanding of subscribers and potential subscribers—
as individuals and as groups—to make strategic purchas-
ing, licensing and content development decisions. It has
created two highly successful dramatic series—House of
Cards and Orange is the New Black—that are informed
in part by the company’s extraordinary understanding of
its subscribers.
While those efforts and the business minds that drive
them make up the heart of the company’s business, the
technology that supports these initiatives must be more
powerful and reliable than that of its competitors. The
data and analytics platform must be able to:
•• Rapidly and reliably handle staggering workloads; it
must support insightful analysis of billions of transac-
tional events each day—every search, browse, stop and
start—in whatever data format that records the events.
Netflix has created two highly
successful dramatic series—
House of Cards and Orange is
the New Black—that are informed
in part by the company’s
extraordinary understanding of
its subscribers.
3. Netflix Demonstrates Power of Analytics3 teradata.com
•• Work with a variety of analytics approaches, including
neural networks, Python, Pig, as well as varied Business
Intelligence tools, like MicroStrategy.
•• Easily scale and contract as necessary with exceptional
elasticity.
•• Provide a safe and redundant repository for all of the
company’s data.
•• Fit within the company’s cost structure and desired
profit margins.
Bringing Teradata Analytics to
the Cloud
With these considerations in mind, Netflix and Teradata
teamed up to launch a successful venture to bring
Netflix’s Teradata Data Warehouse into the cloud.
Power and Maturity
Teradata’s well-earned reputation for exceptional perfor-
mance is especially important to a company like Netflix,
which pounds its analytics platform with hundreds of
concurrent queries. Netflix also needed data warehousing
and analytics tools that enable complex workload
management—essential for creating different queues
for different users, and thus allowing for the constant
and reliable filtering of what each user needs.
Hybrid Analytical Ecosystems and a Unified
Data Architecture
Netflix’s reliance on a hybrid analytical ecosystem that
leverages Hadoop where appropriate, but refuses to
compromise on speed and agility was the perfect fit for
Teradata. Netflix’s cloud environment relies on a Teradata-
Hadoop connector that enables Netflix to seamlessly
move cloud-based data from another provider into the
Teradata Cloud. The result is that Netflix can do much
of its analytics off a world-class data warehouse in the
Teradata Cloud that offers peace-of-mind redundancy,
the ability to expand and contract in response to changing
business conditions and a significantly reduced need for
data movement. And, Netflix’s no-holds-barred approach
to allowing their analysts to use whatever analytical
tools fit the bill demanded a unique analytics platform
that could accommodate them. Having a partner that
works efficiently with the full complement of analytical
applications—both its own and other leading software
providers—was critical.