Introduction to Big Data Infrastructure

•

5 likes•1,225 views

Slides from a talk which introduces infrastructure that powers your data applications. The data infrastructure ties together the distributed components, systems and processes to drive value from data. The topics covered were data collection, immutable logs, scaling ETL processes and real-time analytics. Example use cases of Kafka, Storm, Elasticsearch, and Amazon Redshift were presented.

Data & Analytics

Introduction to
Big Data Infrastructure
Vancouver
SMAC (Social, Mobile, Analytics & Cloud) Meetup
Oct 22, 2014
Ganesh Swami
www.silota.com

Hi
• Programming professionally for 10+ years
• x86 assembly, STL, boost, python-boost, python
• Built emacs-‐wiki-‐blog: first blogging engine for
Emacs!

What is Big Data?
3V: Volume, Velocity, Variety

The Big Data Zoo
Amazon Kinesis Riak Cassandra Hive
Apache Spark Apache Hadoop Pig Apache Storm
Kibana Tableu Apache Kafka
Elasticsearch Amazon EMR Redshift
Dynamo DB Riak HBase

The Zoo Organized
Ingest Store
Process/
Enrich
Visualize
Kafka S3 Hive/Pig/EMR Tableu
Data Answers
Kinesis DynamoDB Spark Kibana
Flume HDFS Storm
Scribe Redshift

Data Ingestion
Ingest
Layer
Mobile Apps
Websites
Internet of Things

Elasticsearch
Open-source search and analytics solution

Amazon Redshift
Petabyte-scale data warehouse solution

What is Silota
• Building blocks of analytics
• A simple REST API
• to ingest
• to analyze
• to export
• based on Kafka, Storm and Elasticsearch

Silota -vs- Mixpanel
• Mixpanel for product people
• great UI
• cookie-cutter analysis for verticals (gaming, e-commerce)
• Silota is an API
• more low-level, full-power
• first class API: responses, pagination, errors, etc.

Keep in Touch!
Ganesh Swami
ganesh@silota.com
www.silota.com

Build a simple open data lake on AWS using a combination of open-source software (OSS), including Red Hat’s Debezium, Apache Kafka, and Kafka Connect for change data capture (CDC), and Apache Hive, Apache Spark, Apache Hudi, and Hudi’s DeltaStreamer for managing our data lake. We will use fully-managed AWS services to host the open data lake components, including Amazon RDS, Amazon MKS, Amazon EKS, and EMR. Link to the blog post and video: https://garystafford.medium.com/building-open-data-lakes-with-debezium-and-apache-hudi-c3370d3f86fb

Quix presto ide, presto summit IL

Ori Reshef

AWS re:Invent 2016: Visualizing Big Data Insights with Amazon QuickSight (BDM...

Amazon Web Services

Amazon QuickSight is a fast BI service that makes it easy for you to build visualizations, perform ad-hoc analysis, and quickly get business insights from your data. QuickSight is built to harness the power and scalability of the cloud, so you can easily run analysis on large datasets, and support hundreds of thousands of users. In this session, we’ll demonstrate how you can easily get started with Amazon QuickSight, uploading files, connecting to S3 and Redshift and creating analyses from visualizations that are optimized based on the underlying data. Once we’ve built our analysis and dashboard, we’ll show you easy it is to share it with colleagues and stakeholders in just a few seconds. And with SPICE – QuckSight’s in-memory calculation engine – you can go from data to insights, faster than ever.

Big problems Big data, simple AWS solution

Jean-Claude Sotto

RedisConf17 - Real-time Intelligence with Redis-ML and Apache Spark

Redis Labs

Vulnerabilities such as Spectre and Meltdown continue to plague many production servers, based on Intel CPUs. Our solution involves software-based monitoring of hardware counters and sending that data to Apache Spark clusters for threat detection. We leverage Spark's support for support vector machine (SVM) inference. Our machine learning models are trained off-line by a data scientist within a Jupyter notebook environment. As new models are validated, they can be easily deployed to the Spark cluster from the notebook. We have standardized model export and import using the ONNX machine learning open file format. In our presentation, we will demo the full pipeline, from model training to deployment. We will discuss the various challenges when deploying ML-based cyber-threat detection at scale using Apache Spark. For example, we found that gaps in detection can occur when Spark models are updated. We will describe a novel data ingestion architecture, based on Apache Kafka, that we developed to deal with this issue.

JanusGraph: Looking Backward, Reaching Forward

Jason Plurad

The JanusGraph project started at the Linux Foundation earlier this year, but it is not the new kid on the block. We'll start with a look at the origins and evolution of this open source graph database through the lens of a few IBM graph use cases. We'll discuss the new features in latest release of JanusGraph, and then take a look at future directions to explore together with the open community. Presented on October 18, 2017 at the Graph Technologies Meetup in Santa Clara, CA. https://www.meetup.com/_CAIDI/events/243122187/

Earth Observation in the Cloud

Amazon Web Services

Presto & differences between popular SQL engines (Spark, Redshift, and Hive)

Holden Ackerman

This is a presentation given at a Big Data Boulder / Denver Meetup event by Ashish Dubey, a Senior Solutions Architect at Qubole. The following slides cover a background of Presto and its architecture, and how it differs in both performance and cost from traditional Hadoop / Hive for Adhoc queries as well as SparkSQL, Impala, Tez, and Redshift. There are also several slides about how Qubole has been involved with the open-source Apache Presto project, along with performance optimizing contributions. Qubole is a big data analytics software that has solved many headaches around the traditional model of big data (Hadoop, Spark, Presto) and cloud computing in popular IaaS providers: AWS, Google Cloud, Microsoft Azure, and Oracle BMC.

JanusGraph, Jupyter Meetup NYC

Jason Plurad

Janus graph lookingbackwardreachingforward

Demai Ni

JanusGraph: Looking Backward and Reaching Forward - by Jason Plurad (@pluradj): The JanusGraph project started at the Linux Foundation earlier this year, but it is not the new kid on the block. We'll start with a look at the origins and evolution of this open source graph database through the lens of a few IBM graph use cases. We'll discuss the new features in latest release of JanusGraph, and then take a look at future directions to explore together with the open community.

Lessons learnt - building a data lake with redshift, emr, and athena - aws co...

AWSCOMSUM

Real Time Data Infrastructure team overview

Monal Daxini

Shifting Data Science into High Gear

Spark Summit

Taking the Performance of your Data Warehouse to the Next Level with Amazon R...

Amazon Web Services

Stream Processing with Apache Spark, Kafka, Avro, and Apicurio Registry on AW...

Gary Stafford

We will read and write messages to and from Amazon MSK in Apache Avro format. We will store the Avro-format Kafka message’s key and value schemas in Apicurio Registry and retrieve the schemas instead of hard-coding the schemas in the PySpark scripts. We will also use the registry to store schemas for CSV-format data files. Link to the blog post and video: https://itnext.io/stream-processing-with-apache-spark-kafka-avro-and-apicurio-registry-on-amazon-emr-and-amazon-13080defa3be

Spark at Airbnb

Hao Wang

Apache Spark Listeners: A Crash Course in Fast, Easy Monitoring

Databricks

The Spark Listener interface provides a fast, simple and efficient route to monitoring and observing your Spark application - and you can start using it in minutes. In this talk, we'll introduce the Spark Listener interfaces available in core and streaming applications, and show a few ways in which they've changed our world for the better at SpotX. If you're looking for a "Eureka!" moment in monitoring or tracking of your Spark apps, look no further than Spark Listeners and this talk!

Azure Global Bootcamp - CIS Handson

Jan Pieter Posthuma

Analytics at the Real-Time Speed of Business: Spark Summit East talk by Manis...

Spark Summit

Redis accelerates Apache Spark execution by 45 times, when used as a shared distributed in-memory datastore for Spark in analyses like time series data range queries. With the redis module for machine learning, redis-ml, implementation of spark-ml models gains a new real time serving layer that offloads processing of models directly in Redis, allows multiple applications to reuse the same models and speeds up classification and execution of these models by 13x. Join this session to learn more about the Redis Labs’ connector for Apache Spark that enhances production implementations of real-time big data processing.

Presto Summit 2018 - 08 - FINRA

kbajda

Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)

Jeff Magnusson

Overview of the data platform as a service architecture at Netflix. We examine the tools and services built around the Netflix Hadoop platform that are designed to make access to big data at Netflix easy, efficient, and self-service for our users. From the perspective of a user of the platform, we walk through how various services in the architecture can be used to build a recommendation engine. Sting, a tool for fast in memory aggregation and data visualization, and Lipstick, our workflow visualization and monitoring tool for Apache Pig, are discussed in depth. Lipstick is now part of Netflix OSS - clone it on github, or learn more from our techblog post: http://techblog.netflix.com/2013/06/introducing-lipstick-on-apache-pig.html.

963Annu Ahmed

Vancouver keynote - AWS Innovate - Sam Elmalak

Amazon Web Services

Modern data architectures for real time analytics and engagement

Amazon Web Services

What's hot

The Little Warehouse That Couldn't Or: How We Learned to Stop Worrying and Mo...

Spark Summit

Building near real-time HTAP solutions using Synapse Link for Azure Cosmos DB

Timothy McAliley

Scaling ML-Based Threat Detection For Production Cyber Attacks

Databricks

JanusGraph: Looking Backward, Reaching Forward

Jason Plurad

Earth Observation in the Cloud

Amazon Web Services

Presto & differences between popular SQL engines (Spark, Redshift, and Hive)

Holden Ackerman

JanusGraph, Jupyter Meetup NYC

Jason Plurad

Janus graph lookingbackwardreachingforward

Demai Ni

Lessons learnt - building a data lake with redshift, emr, and athena - aws co...

AWSCOMSUM

Real Time Data Infrastructure team overview

Monal Daxini

Shifting Data Science into High Gear

Spark Summit

Taking the Performance of your Data Warehouse to the Next Level with Amazon R...

Amazon Web Services

Stream Processing with Apache Spark, Kafka, Avro, and Apicurio Registry on AW...

Gary Stafford

Spark at Airbnb

Hao Wang

Apache Spark Listeners: A Crash Course in Fast, Easy Monitoring

Databricks

Azure Global Bootcamp - CIS Handson

Jan Pieter Posthuma

Analytics at the Real-Time Speed of Business: Spark Summit East talk by Manis...

Spark Summit

Presto Summit 2018 - 08 - FINRA

kbajda

Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)

Jeff Magnusson

What's hot (19)

The Little Warehouse That Couldn't Or: How We Learned to Stop Worrying and Mo...

Building near real-time HTAP solutions using Synapse Link for Azure Cosmos DB

Scaling ML-Based Threat Detection For Production Cyber Attacks

JanusGraph: Looking Backward, Reaching Forward

Earth Observation in the Cloud

Presto & differences between popular SQL engines (Spark, Redshift, and Hive)

JanusGraph, Jupyter Meetup NYC

Janus graph lookingbackwardreachingforward

Lessons learnt - building a data lake with redshift, emr, and athena - aws co...

Real Time Data Infrastructure team overview

Shifting Data Science into High Gear

Taking the Performance of your Data Warehouse to the Next Level with Amazon R...

Stream Processing with Apache Spark, Kafka, Avro, and Apicurio Registry on AW...

Spark at Airbnb

Apache Spark Listeners: A Crash Course in Fast, Easy Monitoring

Azure Global Bootcamp - CIS Handson

Analytics at the Real-Time Speed of Business: Spark Summit East talk by Manis...

Presto Summit 2018 - 08 - FINRA

Watching Pigs Fly with the Netflix Hadoop Toolkit (Hadoop Summit 2013)

Similar to Introduction to Big Data Infrastructure

963Annu Ahmed

Vancouver keynote - AWS Innovate - Sam Elmalak

Amazon Web Services

Modern data architectures for real time analytics and engagement

Amazon Web Services

BDA305 Building Data Lakes and Analytics on AWS

Amazon Web Services

Over 90% of today’s data was generated in the last 2 years, and the rate of data growth isn’t slowing down. In this session, we’ll step through the challenges and best practices on how to capture all the data that is being generated, understand what data you have, and start driving insights and even predict the future using purpose built AWS Services. We’ll frame the session and demonstrations around common pitfalls of building Data Lakes and how to successful drive analytics and insights from the data. This session will focus on the architecture patterns bringing together key AWS Services and rather than a deep dive on any single service. We’ll show how services such as Amazon S3, Amazon Glue, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon Kinesis, and Amazon Machine Learning services are put together to build a successful data lake for various role including both data scientists and business users.

Apache Spark – The New Enterprise Backbone for ETL, Batch Processing and Real...

Impetus Technologies

In spite of investments in big data lakes, there is wide use of expensive proprietary products for data ingestion, integration, and transformation (ETL) while bringing and processing data on the lake. Enterprises have successfully tested Apache Spark for its versatility and strengths as a distributed computing framework that can completely handle all needs for data processing, analytics, and machine learning workloads. Since the Hadoop distributions and the public cloud already include Apache Spark, there is nothing new to be procured. However, the skills required to put Spark to good use are typically unavailable today. In this webinar, we will discuss how Apache Spark can be an inexpensive enterprise backbone for all types of data processing workloads. We will also demo how a visual framework on top of Apache Spark makes it much more viable. The following scenarios will be covered: On-Prem Data quality and ETL with Apache Spark using pre-built operators Advanced monitoring of Spark pipelines On Cloud Visual interactive development of Apache Spark Structured Streaming pipelines IoT use-case with event-time, late-arrival and watermarks Python based predictive analytics running on Spark

BDA303 Serverless big data architectures: Design patterns and best practices

Amazon Web Services

Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. But how can you incorporate serverless concepts into your big data architectures? In this session, we explore the key concepts and benefits of serverless architectures for big data, diving into design patterns to ingest, store, process, and visualize your data. Along the way, we explain when and how you can use serverless technologies to streamline data processing, minimize infrastructure management, and improve agility and robustness. We will share reference architectures using a combination of services that include AWS Lambda, Amazon Kinesis, Amazon Athena, Amazon QuickSight, and AWS Glue.

Building a Real Time Dashboard with Amazon Kinesis, Amazon Lambda and Amazon ...

Amazon Web Services

Open source big data landscape and possible ITS applications

SoftwareMill

Modern Data Architectures for Real Time Analytics & Engagement

Amazon Web Services

Building Data Warehouses and Data Lakes in the Cloud - DevDay Austin 2017 Day 2Amazon Web Services

Building a Data Processing Pipeline on AWS

Amazon Web Services

AWS provides a broad platform of managed services to help you build, secure, and seamlessly scale end-to-end Big Data applications quickly and with ease. Want to get ramped up on how to use Amazon's big data web services? Learn when to use which service? Want to write your first big data application on AWS? Join us in this session as we discuss reference architecture, design patterns, and best practices for pulling together various AWS services to meet your big data challenges.

Building a Data Processing Pipeline on AWS - AWS Summit SG 2017

Amazon Web Services

FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...

Amazon Web Services

FINRA’s analytics platform unlocks the value in capital markets data by accelerating trade analytics and providing a foundation for machine learning at scale. The platform enables FINRA’s analysts to perform discovery on petabytes of trade data to identify instances of potential fraud, market manipulation, and insider trading. By centralizing all data in S3, FINRA’s architecture offers improved agility, scalability, and cost effectiveness. Analytics services such as Amazon EMR and Amazon Redshift have freed FINRA’s data scientists from the constraints of desktop tools, allowing them to apply machine learning techniques to develop and test new surveillance patterns. All of this is done while meeting FINRA’s security and compliance responsibilities as a financial regulator. At the end of this session, you’ll have an understanding of how to apply FINRA’s architecture to trade analytics and other financial services use cases, including meeting regulatory requirements such as the Consolidated Audit Trail (CAT) reporting.

2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines

Timothy Spann

2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines https://www.aicamp.ai/event/eventdetails/W2024022214 apache nifi llm generative ai gen ai ml dl machine learning apache kafka apache flink postgresql python AI Meetup (NYC): GenAI, LLMs, ML and Data Feb 22, 05:30 PM EST Welcome to the monthly in-person AI meetup in New York City, in collaboration with Microsoft. Join us for deep dive tech talks on AI, GenAI, LLMs and machine learning, food/drink, networking with speakers and fellow developers Agenda: * 5:30pm~6:00pm: Checkin, Food/drink and networking * 6:00pm~6:10pm: Welcome/community update * 6:10pm~8:30pm: Tech talks * 8:30pm: Q&A, Open discussion Tech Talk: Searching and Reasoning Over Multimedia Data with Vector Databases and LMMs Speaker: Zain Hasan (Weaviate LinkedIn) Abstract: In this talk, Zain Hasan will discuss how we can use open-source multimodal embedding models in conjunction with large generative multimodal models that can that can see, hear, read, and feel data(!), to perform cross-modal search(searching audio with images, videos with text etc.) and multimodal retrieval augmented generation (MM-RAG) at the billion-object scale with the help of open source vector databases. I will also demonstrate, with live code demos, how being able to perform this cross-modal retrieval in real-time can enables users to use LLMs that can reason over their enterprise multimodal data. This talk will revolve around how we can scale the usage of multimodal embedding and generative models in production. Tech Talk: Codeless Generative AI Pipelines Speaker: Timothy Spann (Cloudera LinkedIn) Abstract: Join us for an insightful talk on leveraging the power of real-time streaming tools, specifically Apache NiFi, to revolutionize GenAI data engineering. In this session, we’ll explore how the integration of Apache NiFi can automate the entire process of prompt building, making it a seamless and efficient task. Speakers/Topics: Stay tuned as we are updating speakers and schedules. If you have a keen interest in speaking to our community, we invite you to submit topics for consideration: Submit Topics Sponsors: We are actively seeking sponsors to support our community. Whether it is by offering venue spaces, providing food/drink, or cash sponsorship. Sponsors will have the chance to speak at the meetups, receive prominent recognition, and gain exposure to our extensive membership base of 20,000+ local or 300K+ developers worldwide. Venue: Microsoft NYC - Times Square, 11 Times Square, New York, NY 10036 Room Name: Central Park West 6501 Community on Slack/Discord - Event chat: chat and connect with speakers and attendees - Sharing blogs, events, job openings, projects collaborations Join Slack (search and join the #newyork channel) | Join Discord

963Annu Ahmed

Real-time Analytics with Open-Source

Amazon Web Services

Working with big volumes of data is a complicated task, but it's even harder if you have to do everything in real time and try to figure it all out yourself. Over the past decades many open-source projects helped solve problems within the data analytics lifecycle around ingestion, storage, processing and visualisation of data. This session will use practical examples to discuss architectural best practices and lessons learned when solving real-time analytics and data visualisation decision-making problems with open-source at scale with the power of Amazon Web Services. It furthermore dives into a demo, using source code from the AWS Labs to visualise live data streams at scale. Olivier Klein, Solutions Architect, Amazon Web Services, Greater China

Big Data & Analytics: End to End on AWS - Technical 101

Amazon Web Services

Agile BI - Pop-up Loft Tel Aviv

Amazon Web Services

Mai-Lan Tomsen Bukovec- Keynote-AWS Summit Manila

Amazon Web Services

Evolving Your Big Data Use Cases from Batch to Real-Time - AWS May 2016 Webi...

Amazon Web Services

Batch querying and reporting is no longer enough for many organizations. Reducing time to insight – the time it takes to turn data into actionable insights – is becoming increasingly important to remain competitive. That’s why organizations are quickly evolving their data applications to support a broader set of real-time analytic use cases. In this webinar, we will review some of the common use cases for real-time analytics such as click-stream analysis, event data processing, and real-time analytics. We will show proven architectures for collecting, storing, and processing real-time data using a combination of AWS managed services, including Amazon Kinesis Streams, Amazon Kinesis Firehose, Amazon EMR, and AWS Lambda, as well open source tools, such as Apache Spark. Then, we will discuss common approaches and best practices to incorporate real-time analytics into your existing batch applications. Learning Objectives: • Understand how to incorporate real-time analytics into existing applications • Best practices to combine batch with real-time data flows • Learn common architectures and use cases for real-time analytics

Similar to Introduction to Big Data Infrastructure (20)

963

Vancouver keynote - AWS Innovate - Sam Elmalak

Modern data architectures for real time analytics and engagement

BDA305 Building Data Lakes and Analytics on AWS

Apache Spark – The New Enterprise Backbone for ETL, Batch Processing and Real...

BDA303 Serverless big data architectures: Design patterns and best practices

Building a Real Time Dashboard with Amazon Kinesis, Amazon Lambda and Amazon ...

Open source big data landscape and possible ITS applications

Modern Data Architectures for Real Time Analytics & Engagement

Building Data Warehouses and Data Lakes in the Cloud - DevDay Austin 2017 Day 2

Building a Data Processing Pipeline on AWS

Building a Data Processing Pipeline on AWS - AWS Summit SG 2017

FSV307-Capital Markets Discovery How FINRA Runs Trade Analytics and Surveilla...

2024 Feb AI Meetup NYC GenAI_LLMs_ML_Data Codeless Generative AI Pipelines

963

Real-time Analytics with Open-Source

Big Data & Analytics: End to End on AWS - Technical 101

Agile BI - Pop-up Loft Tel Aviv

Mai-Lan Tomsen Bukovec- Keynote-AWS Summit Manila

Evolving Your Big Data Use Cases from Batch to Real-Time - AWS May 2016 Webi...

Recently uploaded

哪里卖(usq毕业证书)南昆士兰大学毕业证研究生文凭证书托福证书原版一模一样

axoqas

原版定制【Q微信:741003700】《(usq毕业证书)南昆士兰大学毕业证研究生文凭证书》【Q微信:741003700】成绩单、雅思、外壳、留信学历认证永久存档查询，采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。【业务选择办理准则】一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【Q微信741003700】文凭即可二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信741003700】即可三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才【关于价格问题（保证一手价格）】我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子我给客户的都是第一手的代理价格，因为我想坦诚对待大家不想跟大家在价格方面浪费时间对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。

FP Growth Algorithm and its Applications

MaleehaSheikh2

Criminal IP - Threat Hunting Webinar.pdf

Criminal IP

一比一原版(UMich毕业证)密歇根大学|安娜堡分校毕业证成绩单

ewymefz

UMich毕业证【微信95270640】办理UMich毕业证【Q微信95270640】密歇根大学|安娜堡分校毕业证书原版↑制作密歇根大学|安娜堡分校学历认证文凭办理密歇根大学|安娜堡分校留信网认证,留学回国办理毕业证成绩单文凭学历认证【Q微信95270640】专业为海外学子办理毕业证成绩单、文凭制作，学历仿制，回国人员证明、做文凭，研究生、本科、硕士学历认证、留信认证、结业证、学位证书样本、美国教育部认证百分百真实存档可查】【本科硕士】密歇根大学|安娜堡分校密歇根大学|安娜堡分校硕士毕业证成绩单（GPA修改）；学历认证（教育部认证）；大学Offer录取通知书留信认证使馆认证；雅思语言证书等高仿类证书。办理流程： 1客户提供办理密歇根大学|安娜堡分校密歇根大学|安娜堡分校硕士毕业证成绩单信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）； 2开始安排制作毕业证成绩单电子图； 3毕业证成绩单电子版做好以后发送给您确认； 4毕业证成绩单电子版您确认信息无误之后安排制作成品； 5成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄）真实网上可查的证明材料 1教育部学历学位认证留服官网真实存档可查永久存档。 2留学回国人员证明（使馆认证）使馆网站真实存档可查。我们对海外大学及学院的毕业证成绩单所使用的材料尺寸大小防伪结构（包括：密歇根大学|安娜堡分校密歇根大学|安娜堡分校硕士毕业证成绩单隐形水印阴影底纹钢印LOGO烫金烫银LOGO烫金烫银复合重叠。文字图案浮雕激光镭射紫外荧光温感复印防伪）都有原版本文凭对照。质量得到了广大海外客户群体的认可同时和海外学校留学中介做到与时俱进及时掌握各大院校的（毕业证成绩单资格证结业证录取通知书在读证明等相关材料）的版本更新信息能够在第一时间掌握最新的海外学历文凭的样版尺寸大小纸张材质防伪技术等等并在第一时间收集到原版实物以求达到客户的需求。本公司还可以按照客户原版印刷制作且能够达到客户理想的要求。有需要办理证件的客户请联系我们在线客服中心微信：95270640 或咨询在线在我脑海中回旋很幸运我有这样的机会能将埋在心底深深的感激之情得以表达从婴儿的“哇哇坠地到哺育我长大您们花去了多少的心血与汗水编织了多少个日日夜夜从上小学到初中乃至大学燃烧着自己默默奉献着光和热全天下的父母都是仁慈的无私的伟大的所以无论何时何地都不要忘记您们是这样的无私将一份沉甸甸的爱和希望传递到我们的眼里和心中而我应做的就是感恩父母回报社会共创和谐父母对我们的恩情深厚而无私孝敬父母是我们做人元

一比一原版(RUG毕业证)格罗宁根大学毕业证成绩单

vcaxypu

RUG毕业证【微信95270640】办文凭{格罗宁根大学毕业证}Q微Q微信95270640RUG毕业证书成绩单/学历认证RUG Diploma未毕业、挂科怎么办？+QQ微信：Q微信95270640-大学Offer（申请大学）、成绩单（申请考研）、语言证书、在读证明、使馆公证、办真实留信网认证、真实大使馆认证、学历认证办理国外格罗宁根大学毕业证书 #成绩单改成绩 #教育部学历学位认证 #毕业证认证 #留服认证 #使馆认证（留学回国人员证明） #（证）等真实教育部认证教育部存档中国教育部留学服务中心认证（即教育部留服认证）网站100%可查. 真实使馆认证（即留学人员回国证明）使馆存档可通过大使馆查询确认. 留信网认证国家专业人才认证中心颁发入库证书留信网永久存档可查. 格罗宁根大学格罗宁根大学毕业证学历书毕业证 #成绩单等全套材料从防伪到印刷从水印到钢印烫金跟学校原版100%相同. 国际留学归国服务中心：实体公司注册经营行业标杆精益求精！国外毕业证学位证成绩单办理流程： 1客户提供办理格罗宁根大学格罗宁根大学毕业证学历书信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）； 2开始安排制作格罗宁根大学毕业证成绩单电子图； 3格罗宁根大学毕业证成绩单电子版做好以后发送给您确认； 4格罗宁根大学毕业证成绩单电子版您确认信息无误之后安排制作成品； 5格罗宁根大学成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快递邮寄格罗宁根大学格罗宁根大学毕业证学历书）。也得开灯开风扇山娃不想浪费电总将小方桌搁在门口看书写作业有一次山娃坐在门口写作业写着写着竟伏在桌上睡着了迷迷糊糊中山娃似乎听到了父亲的脚步声当他晃晃悠悠站起来时才诧然发现一位衣衫破旧的妇女挎着一只硕大的蛇皮袋手里拎着长铁钩正站在门口朝黑色的屋内张望不好坏人小偷山娃一怔却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死受

Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...

pchutichetpong

M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years. Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success. MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies. According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”

一比一原版(UniSA毕业证书)南澳大学毕业证如何办理

slg6lamcq

原版定制【微信:41543339】【(UniSA毕业证书)南澳大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】【业务选择办理准则】一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才留信网服务项目： 1、留学生专业人才库服务（留信分析） 2、国（境）学习人员提供就业推荐信服务 3、留学人员区块链存储服务 → 【关于价格问题（保证一手价格）】我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子我给客户的都是第一手的代理价格，因为我想坦诚对待大家不想跟大家在价格方面浪费时间对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！

Best best suvichar in gujarati english meaning of this sentence as Silk road ...

AbhimanyuSinha9

SOCRadar Germany 2024 Threat Landscape Report

SOCRadar

As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape. In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity. 🔑 Key findings include: 🔍 Increased frequency and complexity of cyber threats. 🔍 Escalation of state-sponsored and criminally motivated cyber operations. 🔍 Active dark web exchanges of malicious tools and tactics. Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities. This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.

一比一原版(UofS毕业证书)萨省大学毕业证如何办理

v3tuleee

原版定制【微信:41543339】【(UofS毕业证书)萨省大学毕业证】【微信:41543339】成绩单、外壳、offer、留信学历认证（永久存档真实可查）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。【我们承诺采用的是学校原版纸张（纸质、底色、纹路），我们拥有全套进口原装设备，特殊工艺都是采用不同机器制作，仿真度基本可以达到100%，所有工艺效果都可提前给客户展示，不满意可以根据客户要求进行调整，直到满意为止！】【业务选择办理准则】一、工作未确定，回国需先给父母、亲戚朋友看下文凭的情况，办理一份就读学校的毕业证【微信41543339】文凭即可二、回国进私企、外企、自己做生意的情况，这些单位是不查询毕业证真伪的，而且国内没有渠道去查询国外文凭的真假，也不需要提供真实教育部认证。鉴于此，办理一份毕业证【微信41543339】即可三、进国企，银行，事业单位，考公务员等等，这些单位是必需要提供真实教育部认证的，办理教育部认证所需资料众多且烦琐，所有材料您都必须提供原件，我们凭借丰富的经验，快捷的绿色通道帮您快速整合材料，让您少走弯路。留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才留信网服务项目： 1、留学生专业人才库服务（留信分析） 2、国（境）学习人员提供就业推荐信服务 3、留学人员区块链存储服务 → 【关于价格问题（保证一手价格）】我们所定的价格是非常合理的，而且我们现在做得单子大多数都是代理和回头客户介绍的所以一般现在有新的单子我给客户的都是第一手的代理价格，因为我想坦诚对待大家不想跟大家在价格方面浪费时间对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。选择实体注册公司办理，更放心，更安全！我们的承诺：客户在留信官方认证查询网站查询到认证通过结果后付款，不成功不收费！

一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理

ahzuo

UIUC毕业证offer【微信95270640】☀《伊利诺伊大学|厄巴纳-香槟分校毕业证购买》GoogleQ微信95270640《UIUC毕业证模板办理》加拿大文凭、本科、硕士、研究生学历都可以做,二、业务范围： ★、全套服务：毕业证、成绩单、化学专业毕业证书伪造《伊利诺伊大学|厄巴纳-香槟分校大学毕业证》Q微信95270640《UIUC学位证书购买》 (诚招代理)办理国外高校毕业证成绩单文凭学位证,真实使馆公证（留学回国人员证明）真实留信网认证国外学历学位认证雅思代考国外学校代申请名校保录开请假条改GPA改成绩ID卡 1.高仿业务:【本科硕士】毕业证,成绩单（GPA修改）,学历认证（教育部认证）,大学Offer,,ID,留信认证,使馆认证,雅思,语言证书等高仿类证书； 2.认证服务: 学历认证（教育部认证）,大使馆认证（回国人员证明）,留信认证（可查有编号证书）,大学保录取,雅思保分成绩单。 3.技术服务：钢印水印烫金激光防伪凹凸版设计印刷激凸温感光标底纹镭射速度快。办理伊利诺伊大学|厄巴纳-香槟分校伊利诺伊大学|厄巴纳-香槟分校毕业证offer流程： 1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）； 2开始安排制作毕业证成绩单电子图； 3毕业证成绩单电子版做好以后发送给您确认； 4毕业证成绩单电子版您确认信息无误之后安排制作成品； 5成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄） -办理真实使馆公证（即留学回国人员证明） -办理各国各大学文凭（世界名校一对一专业服务,可全程监控跟踪进度） -全套服务：毕业证成绩单真实使馆公证真实教育部认证。让您回国发展信心十足！（详情请加一下文凭顾问+微信:95270640）欢迎咨询！的鬼地方父亲的家在高楼最底屋最下面很矮很黑是很不显眼的地下室父亲的家安在别人脚底下须绕过高楼旁边的垃圾堆下八个台阶才到父亲的家很狭小除了一张单人床和一张小方桌几乎没有多余的空间山娃一下子就联想起学校的男小便处山娃很想笑却怎么也笑不出来山娃很迷惑父亲的家除了一扇小铁门连窗户也没有墓穴一般阴森森有些骇人父亲的城也便成了山娃的城父亲的家也便成了山娃的家父亲让山娃呆在屋里做作业看电视最多只能在门口透透气间

原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样

u86oixdj

学校原件一模一样【微信：741003700 】《(Deakin毕业证书)迪肯大学毕业证学位证》【微信：741003700 】学位证，留信认证（真实可查，永久存档）原件一模一样纸张工艺/offer、雅思、外壳等材料/诚信可靠,可直接看成品样本，帮您解决无法毕业带来的各种难题！外壳，原版制作，诚信可靠，可直接看成品样本。行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备。十五年致力于帮助留学生解决难题，包您满意。本公司拥有海外各大学样板无数，能完美还原。 1:1完美还原海外各大学毕业材料上的工艺：水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠。文字图案浮雕、激光镭射、紫外荧光、温感、复印防伪等防伪工艺。材料咨询办理、认证咨询办理请加学历顾问Q/微741003700 【主营项目】一.毕业证【q微741003700】成绩单、使馆认证、教育部认证、雅思托福成绩单、学生卡等！二.真实使馆公证(即留学回国人员证明,不成功不收费) 三.真实教育部学历学位认证（教育部存档！教育部留服网站永久可查）四.办理各国各大学文凭(一对一专业服务,可全程监控跟踪进度) 如果您处于以下几种情况： ◇在校期间，因各种原因未能顺利毕业……拿不到官方毕业证【q/微741003700】 ◇面对父母的压力，希望尽快拿到； ◇不清楚认证流程以及材料该如何准备； ◇回国时间很长，忘记办理； ◇回国马上就要找工作，办给用人单位看； ◇企事业单位必须要求办理的 ◇需要报考公务员、购买免税车、落转户口 ◇申请留学生创业基金留信网认证的作用: 1:该专业认证可证明留学生真实身份 2:同时对留学生所学专业登记给予评定 3:国家专业人才认证中心颁发入库证书 4:这个认证书并且可以归档倒地方 5:凡事获得留信网入网的信息将会逐步更新到个人身份内，将在公安局网内查询个人身份证信息后，同步读取人才网入库信息 6:个人职称评审加20分 7:个人信誉贷款加10分 8:在国家人才网主办的国家网络招聘大会中纳入资料，供国家高端企业选择人才

一比一原版(BU毕业证)波士顿大学毕业证成绩单

ewymefz

BU毕业证【微信95270640】购买（波士顿大学毕业证成绩单硕士学历）Q微信95270640代办BU学历认证留信网伪造波士顿大学学位证书精仿波士顿大学本科/硕士文凭证书补办波士顿大学 diplomaoffer,Transcript购买波士顿大学毕业证成绩单购买BU假毕业证学位证书购买伪造波士顿大学文凭证书学位证书,专业办理雅思、托福成绩单，学生ID卡，在读证明，海外各大学offer录取通知书，毕业证书，成绩单，文凭等材料:1:1完美还原毕业证、offer录取通知书、学生卡等各种在读或毕业材料的防伪工艺（包括烫金、烫银、钢印、底纹、凹凸版、水印、防伪光标、热敏防伪、文字图案浮雕，激光镭射，紫外荧光，温感光标）学校原版上有的工艺我们一样不会少，不论是老版本还是最新版本，都能保证最高程度还原，力争完美以求让所有同学都能享受到完美的品质服务。专业为留学生办理波士顿大学波士顿大学毕业证offer【100%存档可查】留学全套申请材料办理。本公司承诺所有毕业证成绩单成品全部按照学校原版工艺对照一比一制作和学校一样的羊皮纸张保证您证书的质量！如果你回国在学历认证方面有以下难题请联系我们我们将竭诚为你解决认证瓶颈 1所有材料真实但资料不全无法提供完全齐整的原件。【如：成绩单丶毕业证丶回国证明等材料中有遗失的。】 2获得真实的国外最终学历学位但国外本科学历就读经历存在问题或缺陷。【如：国外本科是教育部不承认的或者是联合办学项目教育部没有备案的或者外本科没有正常毕业的。】 3学分转移联合办学等情况复杂不知道怎么整理材料的。时间紧迫自己不清楚递交流程的。如果你是以上情况之一请联系我们我们将在第一时间内给你免费咨询相关信息。我们将帮助你整理认证所需的各种材料.帮你解决国外学历认证难题。国外波士顿大学波士顿大学毕业证offer办理方法： 1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询波士顿大学波士顿大学毕业证offer）； 2开始安排制作波士顿大学毕业证成绩单电子图； 3波士顿大学毕业证成绩单电子版做好以后发送给您确认； 4波士顿大学毕业证成绩单电子版您确认信息无误之后安排制作成品； 5波士顿大学成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。二条巴掌般大的裤衩衩走出泳池山娃感觉透身粘粘乎乎散发着药水味有点痒山娃顿时留恋起家乡的小河潺潺活水清凉无比日子就这样孤寂而快乐地过着寂寞之余山娃最神往最开心就是晚上无论多晚多累父亲总要携山娃出去兜风逛夜市流光溢彩人潮涌动的都市夜生活总让山娃目不暇接惊叹不已父亲老问山娃想买什么想吃什么山娃知道父亲赚钱很辛苦除了书籍和文具山娃啥也不要能牵着父亲的手满城闲逛他已心满意足了父亲连挑了三套童装叫山娃试穿山伸

一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单

ewymefz

UofM毕业证【微信95270640】办文凭{明尼苏达大学毕业证}Q微Q微信95270640UofM毕业证书成绩单/学历认证UofM Diploma未毕业、挂科怎么办？+QQ微信：Q微信95270640-大学Offer（申请大学）、成绩单（申请考研）、语言证书、在读证明、使馆公证、办真实留信网认证、真实大使馆认证、学历认证办国外明尼苏达大学明尼苏达大学毕业证假文凭教育部学历学位认证留信认证大使馆认证留学回国人员证明修改成绩单信封申请学校offer录取通知书在读证明offer letter。快速办理高仿国外毕业证成绩单： 1明尼苏达大学毕业证+成绩单+留学回国人员证明+教育部学历认证（全套留学回国必备证明材料给父母及亲朋好友一份完美交代）; 2雅思成绩单托福成绩单OFFER在读证明等留学相关材料（申请学校转学甚至是申请工签都可以用到）。 3.毕业证 #成绩单等全套材料从防伪到印刷从水印到钢印烫金高精仿度跟学校原版100%相同。专业服务请勿犹豫联系我！联系人微信号：95270640诚招代理：本公司诚聘当地代理人员如果你有业余时间有兴趣就请联系我们。国外明尼苏达大学明尼苏达大学毕业证假文凭办理过程： 1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）； 2开始安排制作毕业证成绩单电子图； 3毕业证成绩单电子版做好以后发送给您确认； 4毕业证成绩单电子版您确认信息无误之后安排制作成品； 5成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。有一次山娃坐在门口写作业写着写着竟伏在桌上睡着了迷迷糊糊中山娃似乎听到了父亲的脚步声当他晃晃悠悠站起来时才诧然发现一位衣衫破旧的妇女挎着一只硕大的蛇皮袋手里拎着长铁钩正站在门口朝黑色的屋内张望不好坏人小偷山娃一怔却也灵机一动立马仰起头双手拢在嘴边朝楼上大喊：“爸爸爸——有人找——那人一听朝山娃尴尬地笑笑悻悻地走了山娃立马“嘭的一声将铁门锁死心却咚咚地乱跳当山娃跟父亲说起这事时父亲很吃惊抚摸着山娃母

Machine learning and optimization techniques for electrical drives.pptx

balafet

standardisation of garbhpala offhgfffghh

ArpitMalhotra16

Criminal IP - Threat Hunting Webinar.pdf

Criminal IP

Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...

John Andrews

SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation" Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults Description: Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project. Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas

Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation

Boston Institute of Analytics

Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/

一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单

ewymefz

UPenn毕业证【微信95270640】办理宾夕法尼亚大学毕业证原版一模一样、UPenn毕业证制作【Q微信95270640】《宾夕法尼亚大学毕业证购买流程》《UPenn成绩单制作》宾夕法尼亚大学毕业证书UPenn毕业证文凭宾夕法尼亚大学本科毕业证书,学历学位认证如何办理【留学国外学位学历认证、毕业证、成绩单、大学Offer、雅思托福代考、语言证书、学生卡、高仿教育部认证等一切高仿或者真实可查认证服务】代办国外（海外）英国、加拿大、美国、新西兰、澳大利亚、新西兰等国外各大学毕业证、文凭学历证书、成绩单、学历学位认证真实可查。办国外宾夕法尼亚大学宾夕法尼亚大学硕士学位证成绩单教育部学历学位认证留信认证大使馆认证留学回国人员证明修改成绩单信封申请学校offer录取通知书在读证明offer letter。快速办理高仿国外毕业证成绩单： 1宾夕法尼亚大学毕业证+成绩单+留学回国人员证明+教育部学历认证（全套留学回国必备证明材料给父母及亲朋好友一份完美交代）; 2雅思成绩单托福成绩单OFFER在读证明等留学相关材料（申请学校转学甚至是申请工签都可以用到）。 3.毕业证 #成绩单等全套材料从防伪到印刷从水印到钢印烫金高精仿度跟学校原版100%相同。专业服务请勿犹豫联系我！联系人微信号：95270640诚招代理：本公司诚聘当地代理人员如果你有业余时间有兴趣就请联系我们。国外宾夕法尼亚大学宾夕法尼亚大学硕士学位证成绩单办理过程： 1客户提供办理信息：姓名生日专业学位毕业时间等（如信息不确定可以咨询顾问：我们有专业老师帮你查询）； 2开始安排制作毕业证成绩单电子图； 3毕业证成绩单电子版做好以后发送给您确认； 4毕业证成绩单电子版您确认信息无误之后安排制作成品； 5成品做好拍照或者视频给您确认； 6快递给客户（国内顺丰国外DHLUPS等快读邮寄）。我们在哪里父母对我们的爱和思念为我们的生命增加了光彩给予我们自由追求的力量生活的力量我们也不忘感恩正因为这股感恩的线牵着我们使我们在一年的结束时刻义无反顾的踏上了回家的旅途人们常说父母恩最难回报愿我能以当年爸爸妈妈对待小时候的我们那样耐心温柔地对待我将渐渐老去的父母体谅他们以反哺之心奉敬父母以感恩之心孝顺父母哪怕只为父母换洗衣服为父母喂饭送汤按摩酸痛的腰背握着父母的手扶着他们一步一步地慢慢散步.娃

Recently uploaded (20)

哪里卖(usq毕业证书)南昆士兰大学毕业证研究生文凭证书托福证书原版一模一样

FP Growth Algorithm and its Applications

Criminal IP - Threat Hunting Webinar.pdf

一比一原版(UMich毕业证)密歇根大学|安娜堡分校毕业证成绩单

一比一原版(RUG毕业证)格罗宁根大学毕业证成绩单

Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...

一比一原版(UniSA毕业证书)南澳大学毕业证如何办理

Best best suvichar in gujarati english meaning of this sentence as Silk road ...

SOCRadar Germany 2024 Threat Landscape Report

一比一原版(UofS毕业证书)萨省大学毕业证如何办理

一比一原版(UIUC毕业证)伊利诺伊大学|厄巴纳-香槟分校毕业证如何办理

原版制作(Deakin毕业证书)迪肯大学毕业证学位证一模一样

一比一原版(BU毕业证)波士顿大学毕业证成绩单

一比一原版(UofM毕业证)明尼苏达大学毕业证成绩单

Machine learning and optimization techniques for electrical drives.pptx

standardisation of garbhpala offhgfffghh

Criminal IP - Threat Hunting Webinar.pdf

Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...

Predicting Product Ad Campaign Performance: A Data Analysis Project Presentation

一比一原版(UPenn毕业证)宾夕法尼亚大学毕业证成绩单

Introduction to Big Data Infrastructure

1. Introduction to Big Data Infrastructure Vancouver SMAC (Social, Mobile, Analytics & Cloud) Meetup Oct 22, 2014 Ganesh Swami www.silota.com

2. Hi • Programming professionally for 10+ years • x86 assembly, STL, boost, python-boost, python • Built emacs-‐wiki-‐blog: first blogging engine for Emacs!

3. What is Big Data?

4. What is Big Data? 3V: Volume, Velocity, Variety

5. The Big Data Zoo Amazon Kinesis Riak Cassandra Hive Apache Spark Apache Hadoop Pig Apache Storm Kibana Tableu Apache Kafka Elasticsearch Amazon EMR Redshift Dynamo DB Riak HBase

6. The Zoo Organized Ingest Store Process/ Enrich Visualize Kafka S3 Hive/Pig/EMR Tableu Data Answers Kinesis DynamoDB Spark Kibana Flume HDFS Storm Scribe Redshift

8. Data Ingestion Ingest Layer Mobile Apps Websites Internet of Things

9. Elasticsearch Open-source search and analytics solution

10. Kibana

11. Amazon Redshift Petabyte-scale data warehouse solution

12. What is Silota • Building blocks of analytics • A simple REST API • to ingest • to analyze • to export • based on Kafka, Storm and Elasticsearch

13. Silota -vs- Mixpanel • Mixpanel for product people • great UI • cookie-cutter analysis for verticals (gaming, e-commerce) • Silota is an API • more low-level, full-power • first class API: responses, pagination, errors, etc.

14. Keep in Touch! Ganesh Swami ganesh@silota.com www.silota.com

Introduction to Big Data Infrastructure

Recommended

Recommended

More Related Content

What's hot

What's hot (19)

Similar to Introduction to Big Data Infrastructure

Similar to Introduction to Big Data Infrastructure (20)

Recently uploaded

Recently uploaded (20)

Introduction to Big Data Infrastructure