Parallel processing, columnar structure, and petabyte scaling make Amazon Redshift a powerful data warehousing platform.
Get the full value of your company's analytics with Amazon Redshift and Matillion ETL.
- Get an overview of the latest Amazon Redshift features
- Find out how massive amounts of data can be loaded in a matter of minutes with Matilion ETL
- Learn best practices for cloud data warehousing with Amazon Redshift
Matillion ETL is the fastest, easiest, and most efficient way to leverage these benefits and achieve the full potential of your business.
Pick a Winner: How to Choose a Data WarehouseMatillion
Companies are moving their data into the cloud at an astounding rate—and they are faced with more data warehousing options than ever before.
With such a wealth of solutions to choose from, it can be tough to figure out which cloud-based data warehouse best suits your needs. In this webinar, we review data warehouses in detail and offer practical tips on how to choose the right one for your business.
Learn:
- What a data warehouse is, and why you may need one
- The problems solved by data warehouses
- What criteria to use when choosing a data warehouse
- How Matillion can help you work with the data in your warehouse of choice
Everyone is moving their data to the cloud - but with all the different choices for a cloud based data warehouse, how do you know which one to choose? How do you know which warehouse will be the best and most flexible for your needs?
In this webinar learn:
- Why and what is a data warehouse - do you even need one?
- The best criteria when evaluating which data warehouse to choose
- What problems a data warehouse solves
- What is “Big Data” and how does this provide business value
- How Matillion can help you work with your data in your data warehouse of choice
Hassle-Free Data Lake Governance: Automating Your Analytics with a Semantic L...Tyler Wishnoff
Simplify data lake governance, no matter how much data you work with and how many data sources and BI tools you manage. This presentation offers all you need to develop your own strategy for smarter data lake governance. Learn more at: https://kyligence.io/
Parallel processing, columnar structure, and petabyte scaling make Amazon Redshift a powerful data warehousing platform.
Get the full value of your company's analytics with Amazon Redshift and Matillion ETL.
- Get an overview of the latest Amazon Redshift features
- Find out how massive amounts of data can be loaded in a matter of minutes with Matilion ETL
- Learn best practices for cloud data warehousing with Amazon Redshift
Matillion ETL is the fastest, easiest, and most efficient way to leverage these benefits and achieve the full potential of your business.
Pick a Winner: How to Choose a Data WarehouseMatillion
Companies are moving their data into the cloud at an astounding rate—and they are faced with more data warehousing options than ever before.
With such a wealth of solutions to choose from, it can be tough to figure out which cloud-based data warehouse best suits your needs. In this webinar, we review data warehouses in detail and offer practical tips on how to choose the right one for your business.
Learn:
- What a data warehouse is, and why you may need one
- The problems solved by data warehouses
- What criteria to use when choosing a data warehouse
- How Matillion can help you work with the data in your warehouse of choice
Everyone is moving their data to the cloud - but with all the different choices for a cloud based data warehouse, how do you know which one to choose? How do you know which warehouse will be the best and most flexible for your needs?
In this webinar learn:
- Why and what is a data warehouse - do you even need one?
- The best criteria when evaluating which data warehouse to choose
- What problems a data warehouse solves
- What is “Big Data” and how does this provide business value
- How Matillion can help you work with your data in your data warehouse of choice
Hassle-Free Data Lake Governance: Automating Your Analytics with a Semantic L...Tyler Wishnoff
Simplify data lake governance, no matter how much data you work with and how many data sources and BI tools you manage. This presentation offers all you need to develop your own strategy for smarter data lake governance. Learn more at: https://kyligence.io/
Deep Dive into Concepts and Tools for Analyzing Streaming Data on AWS AWS Germany
Querying streaming data with SQL to derive actionable insights at the point of impact in a timely and continuous fashion offers various benefits over querying data in a traditional database. However, although it is desirable for many use cases to transition to a stream based paradigm, stream processing systems and traditional databases are fundamentally different: in a database, the data is (more or less) fixed and the queries are executed in an ad-hoc manner, whereas in stream processing systems, the queries are fixed and the data flows through the system in real-time. This leads to different primitives that are required to model and query streaming data.
In this session, we will introduce basic stream processing concepts and discuss strategies that are commonly used to address the challenges that arise from querying of streaming data. We will discuss different time semantics, processing guarantees and elaborate how to deal with reordering and late arriving of events. Finally, we will compare how different streaming use cases can be implemented on AWS by leveraging Amazon Kinesis Data Analytics and Apache Flink.
This presentation was used during the 'OOP Best Practices in JavaScript' meetup that took place on April 11th, 2022. More information about this meetup group can be found at https://meetup.com/lifemichael
Talk by Adithya Reddy, Software Development Engineer at Branch Financial on the topic "AppSync in real world - pitfalls, unexpected benefits & lessons learnt" at AWS Community Day, Bangalore 2018
Serverless:It All Started in Vegas (DVC306) - AWS re:Invent 2018Amazon Web Services
This talk dives into Trustpilot's journey to serverless compute. The journey starts at re:Invent 2016 and follows how the company fast-tracked its adoption within its engineering organization using a "serverless first" engineering principle. A representative from Trustpilot shares lessons learned and insights gained from running over 200 AWS Lambda functions with 12M invocations/day in production. Also covered are fun stories of what helped the company adopt serverless, how to make those stories actionable, a review of architectural patterns, and a discussion of why they choose serverless over traditional compute every day.
This session is part of re:Invent Developer Community Day, a series led by AWS enthusiasts who share firsthand technical insights on trending topics.
Going from a hypothesis to a working machine learning model that infers answers in production requires a lot of time and effort. Moreover, the ability to answer questions related to specific results—such as, “what version of the code and data produced a particular inference?”—is paramount in highly regulated industries such as Financial Services. Modern development practices like continuous integration and deployment can accelerate the machine learning development process and provide a way to answer questions about data lineage. During this talk, you will learn how to combine Amazon SageMaker (a fully managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale) with Amazon CodeCommit, CodeBuild, and CodePipeline to create a pipeline that automatically triggers changes when either your model code or training data changes.
Presenter: Felix Candelario, Principal Global Account Solutions Architect, AWS
Amazon Kinesis Data Analytics gives us to tools to run SQL queries against active data streams. We'll look at how we can performance real-time log analytics and q build entire streaming applications using SQL, so that you can gain actionable insights promptly.
Level: Intermediate
Speaker: Bill Baldwin - Database Technical Evangelist, AWS
AWS IoT for Frictionless Consumer Experiences in Retail (RET201) - AWS re:Inv...Amazon Web Services
Gaining key real-time insights is a key differentiator in retail decision making. Traditional or legacy retail processes are often batch-based or delayed in data processing systems that offer post insights to events. Placing a best practice messaging substrate into stores and other environments can provide an over-the-top real-time channel for insights into multiple use cases. Similarly, actions can be pushed in real-time back to the store to action responses to those insights gained. In this session, we demonstrate how AWS Greengrass and AWS IoT services continue gathering data from devices in a store, such as point of sales for analysis, even when connectivity to the cloud is not constant. We dive into how you can leverage Lambda functions on local AWS Greengrass devices to stream in-store events in real time to a data lake in Amazon S3. This data can then be used to derive business insights to drive appropriate action.
Architecting for Real-Time Insights with Amazon Kinesis (ANT310) - AWS re:Inv...Amazon Web Services
Amazon Kinesis makes it easy to speed up the time it takes for you to get valuable, real-time insights from your streaming data. In this session, we walk through the most popular applications that customers implement using Amazon Kinesis, including streaming extract-transform-load, continuous metric generation, and responsive analytics. Our customer Autodesk joins us to describe how they created real-time metrics generation and analytics using Amazon Kinesis and Amazon Elasticsearch Service. They walk us through their architecture and the best practices they learned in building and deploying their real-time analytics solution.
The Theory and Math Behind Data Privacy and Security Assurance (SEC301) - AWS...Amazon Web Services
Data privacy and security are top concerns for customers in the cloud. In this session, the AWS Automated Reasoning group shares the advanced technologies, rooted in mathematical proof, that help provide the highest levels of security assurance in today's data-driven world. The Automated Reasoning group co-presents with Bridgewater, a customer that has leveraged these technologies to help confirm that security requirements are being met, an assurance not previously available from conventional tools.
Understanding Graph Databases: AWS Developer Workshop at Web SummitAmazon Web Services
Understanding Graph Databases: AWS Developer Workshop at Web Summit 2018
Speaker: Gabe Hollombe - Technical Evangelist, AWS
Different types of applications do better with different database technologies. Traditional relational databases are often our go-to choice, but if we're storing lots of relationships between data, a graph database might be a better option. In this session, we'll learn how graph databases differ from more familiar SQL and NoSQL options, and we'll review some of the use cases where graph databases really shine. I'll show how to leverage the power of the cloud to set up your own highly available, scalable, and secure graph database, and we'll run some queries on sample data to get more familiar with how to model and query data in a graph database.
Organizations need to gain insight and knowledge from a growing number of Internet of Things (IoT) APIs clickstreams comprised of unstructured and log data sources. However, organizations are often limited by legacy data warehouses and ETL processes that were designed for transactional data. In this session, we’ll introduce the key ETL features of AWS Glue through use cases ranging from scheduled nightly data warehouse loads to near real-time, event-driven ETL flows for your data lake. We’ll also discuss how to build scalable, efficient and serverless ETL pipelines using AWS Glue.
Ten Tips And Tricks for Improving Your GraphQL API with AWS AppSync (MOB401) ...Amazon Web Services
As you move your modern app to production, you need to consider how to scale, secure, and maintain your backend APIs. In this session, we provide some of the tips, tricks, and best practices for running serverless GraphQL APIs reliably on AWS. We cover topics such as versioning, multiple environments, CI/CD, advanced schema design, monitoring, alerting, and advanced search scenarios.
TSAR (TimeSeries AggregatoR) Tech TalkAnirudh Todi
Twitter's 250 million users generate tens of billions of tweet views per day. Aggregating these events in real time - in a robust enough way to incorporate into our products - presents a massive scaling challenge. In this presentation I introduce TSAR (the TimeSeries AggregatoR), a robust, flexible, and scalable service for real-time event aggregation designed to solve this problem and a range of similar ones. I discuss how we built TSAR using Python and Scala from the ground up, almost entirely on open-source technologies (Storm, Summingbird, Kafka, Aurora, and others), and describe some of the challenges we faced in scaling it to process tens of billions of events per day.
Supercell – Scaling Mobile Games (GAM301) - AWS re:Invent 2018Amazon Web Services
In this session, learn how Supercell architected its analytics pipeline on AWS. We dive deep into how Supercell leverages Amazon Elastic Compute Cloud (Amazon EC2), Amazon Kinesis, Amazon Simple Storage Service (Amazon S3), Amazon EMR, and Spark to ingest, process, store, and query petabytes of data. We also dive deep into how Supercell's games are architected to accommodate scaling and failure recovery. We explain how Supercell's teams are organized into small and independent cells and how this affects the technology choices they make to produce value and agility in the development process.
Similar to Biml Tips and Tricks: Not Just for SSIS Packages! (SQLGrillen 2018) (20)
The Battle of the Data Transformation Tools (PASS Data Community Summit 2023)Cathrine Wilhelmsen
The Battle of the Data Transformation Tools (Presented as part of the "Batte of the Data Transformation Tools" Learning Path at PASS Data Community Summit on November 16th, 2023)
Visually Transform Data in Azure Data Factory or Azure Synapse Analytics (PAS...Cathrine Wilhelmsen
Visually Transform Data in Azure Data Factory or Azure Synapse Analytics (Presented as part of the "Batte of the Data Transformation Tools" Learning Path at PASS Data Community Summit on November 15th, 2023)
Building an End-to-End Solution in Microsoft Fabric: From Dataverse to Power ...Cathrine Wilhelmsen
Building an End-to-End Solution in Microsoft Fabric: From Dataverse to Power BI (Presented at SQLSaturday Oregon & SW Washington on November 11th, 2023)
Stressed, Depressed, or Burned Out? The Warning Signs You Shouldn't Ignore (S...Cathrine Wilhelmsen
Stressed, Depressed, or Burned Out? The Warning Signs You Shouldn't Ignore (Presented at SQLBits on March 18th, 2023)
We all experience stress in our lives. When the stress is time-limited and manageable, it can be positive and productive. This kind of stress can help you get things done and lead to personal growth. However, when the stress stretches out over longer periods of time and we are unable to manage it, it can be negative and debilitating. This kind of stress can affect your mental health as well as your physical health, and increase the risk of depression and burnout.
The tricky part is that both depression and burnout can hit you hard without the warning signs you might recognize from stress. Where stress barges through your door and yells "hey, it's me!", depression and burnout can silently sneak in and gradually make adjustments until one day you turn around and see them smiling while realizing that you no longer recognize your house. I know, because I've dealt with both. And when I thought I had kicked them out, they both came back for new visits.
I don't have the Answers™️ or Solutions™️ to how to keep them away forever. But in hindsight, there were plenty of warning signs I missed, ignored, or was oblivious to at the time. In this deeply personal session, I will share my story of dealing with both depression and burnout. What were the warning signs? Why did I miss them? Could I have done something differently? And most importantly, what can I - and you - do to help ourselves or our loved ones if we notice that something is not quite right?
"I can't keep up!" - Turning Discomfort into Personal Growth in a Fast-Paced ...Cathrine Wilhelmsen
"I can't keep up!" - Turning Discomfort into Personal Growth in a Fast-Paced World (Presented at SQLBits on March 17th, 2023)
Do you sometimes think the world is moving so fast that you're struggling to keep up?
Does it make you feel a little uncomfortable?
Awesome!
That means that you have ambitions. You want to learn new things, take that next step in your career, achieve your goals. You can do anything if you set your mind to it.
It just might not be easy.
All growth requires some discomfort. You need to manage and balance that discomfort, find a way to push yourself a little bit every day without feeling overwhelmed. In a fast-paced world, you need to know how to break down your goals into smaller chunks, how to prioritize, and how to optimize your learning.
Are you ready to turn your "I can't keep up" into "I can't believe I did all of that in just one year"?
Lessons Learned: Implementing Azure Synapse Analytics in a Rapidly-Changing S...Cathrine Wilhelmsen
Lessons Learned: Implementing Azure Synapse Analytics in a Rapidly-Changing Startup (Presented at SQLBits on March 11th, 2022)
What happens when you mix one rapidly-changing startup, one data analyst, one data engineer, and one hypothesis that Azure Synapse Analytics could be the right tool of choice for gaining business insights?
We had no idea, but we gave it a go!
Our ambition was to think big, start small, and act fast – to deliver business value early and often.
Did we succeed?
Join us for an honest conversation about why we decided to implement Azure Synapse Analytics alongside Power BI, how we got started, which areas we completely messed up at first, what our current solution looks like, the lessons learned along the way, and the things we would have done differently if we could start all over again.
6 Tips for Building Confidence as a Public Speaker (SQLBits 2022)Cathrine Wilhelmsen
6 Tips for Building Confidence as a Public Speaker (Presented at SQLBits on March 10th, 2022)
Do you feel nervous about getting on stage to deliver a presentation?
That was me a few years ago. Palms sweating. Hands shaking. Voice trembling. I could barely breathe and talked at what felt like a thousand words per second. Now, public speaking is one of my favorite hobbies. Sometimes, I even plan my vacations around events! What changed?
There are no shortcuts to building confidence as a public speaker. However, there are many things you can do to make the journey a little easier for yourself. In this session, I share the top tips I have learned over the years. All it takes is a little preparation and practice.
You can do this!
Adjusting OpenMP PageRank : SHORT REPORT / NOTESSubhajit Sahu
For massive graphs that fit in RAM, but not in GPU memory, it is possible to take
advantage of a shared memory system with multiple CPUs, each with multiple cores, to
accelerate pagerank computation. If the NUMA architecture of the system is properly taken
into account with good vertex partitioning, the speedup can be significant. To take steps in
this direction, experiments are conducted to implement pagerank in OpenMP using two
different approaches, uniform and hybrid. The uniform approach runs all primitives required
for pagerank in OpenMP mode (with multiple threads). On the other hand, the hybrid
approach runs certain primitives in sequential mode (i.e., sumAt, multiply).
STATATHON: Unleashing the Power of Statistics in a 48-Hour Knowledge Extravag...sameer shah
"Join us for STATATHON, a dynamic 2-day event dedicated to exploring statistical knowledge and its real-world applications. From theory to practice, participants engage in intensive learning sessions, workshops, and challenges, fostering a deeper understanding of statistical methodologies and their significance in various fields."
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
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
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
ViewShift: Hassle-free Dynamic Policy Enforcement for Every Data LakeWalaa Eldin Moustafa
Dynamic policy enforcement is becoming an increasingly important topic in today’s world where data privacy and compliance is a top priority for companies, individuals, and regulators alike. In these slides, we discuss how LinkedIn implements a powerful dynamic policy enforcement engine, called ViewShift, and integrates it within its data lake. We show the query engine architecture and how catalog implementations can automatically route table resolutions to compliance-enforcing SQL views. Such views have a set of very interesting properties: (1) They are auto-generated from declarative data annotations. (2) They respect user-level consent and preferences (3) They are context-aware, encoding a different set of transformations for different use cases (4) They are portable; while the SQL logic is only implemented in one SQL dialect, it is accessible in all engines.
#SQL #Views #Privacy #Compliance #DataLake