Pipelines and Data Flows: Introduction to Data Integration in Azure Synapse Analytics (Global Azure Norway 2021)

The world of data architecture began with applications. Next came data warehouses. Then text was organized into a data warehouse. Then one day the world discovered a whole new kind of data that was being generated by organizations. The world found that machines generated data that could be transformed into valuable insights. This was the origin of what is today called the data lakehouse. The evolution of data architecture continues today. Come listen to industry experts describe this transformation of ordinary data into a data architecture that is invaluable to business. Simply put, organizations that take data architecture seriously are going to be at the forefront of business tomorrow. This is an educational event. Several of the authors of the book Building the Data Lakehouse will be presenting at this symposium.

Data Lakehouse Symposium | Day 1 | Part 2

The traditional data warehouse has served us well for many years, but new trends are causing it to break in four different ways: data growth, fast query expectations from users, non-relational/unstructured data, and cloud-born data. How can you prevent this from happening? Enter the modern data warehouse, which is able to handle and excel with these new trends. It handles all types of data (Hadoop), provides a way to easily interface with all these types of data (PolyBase), and can handle “big data” and provide fast queries. Is there one appliance that can support this modern data warehouse? Yes! It is the Analytics Platform System (APS) from Microsoft (formally called Parallel Data Warehouse or PDW) , which is a Massively Parallel Processing (MPP) appliance that has been recently updated (v2 AU1). In this session I will dig into the details of the modern data warehouse and APS. I will give an overview of the APS hardware and software architecture, identify what makes APS different, and demonstrate the increased performance. In addition I will discuss how Hadoop, HDInsight, and PolyBase fit into this new modern data warehouse.

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Delta has been powering many production pipelines at scale in the Data and AI space since it has been introduced for the past few years. Built on open standards, Delta provides data reliability, enhances storage and query performance to support big data use cases (both batch and streaming), fast interactive queries for BI and enabling machine learning. Delta has matured over the past couple of years in both AWS and AZURE and has become the de-facto standard for organizations building their Data and AI pipelines. In today’s talk, we will explore building end-to-end pipelines on the Google Cloud Platform (GCP). Through presentation, code examples and notebooks, we will build the Delta Pipeline from ingest to consumption using our Delta Bronze-Silver-Gold architecture pattern and show examples of Consuming the delta files using the Big Query Connector.

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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.

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With the aid of any number of data management and processing tools, data flows through multiple on-prem and cloud storage locations before it’s delivered to business users. As a result, IT teams — including IT Ops, DataOps, and DevOps — are often overwhelmed by the complexity of creating a reliable data pipeline that includes the automation and observability they require. The answer to this widespread problem is a centralized data pipeline orchestration solution. Join Stonebranch’s Scott Davis, Global Vice President and Ravi Murugesan, Sr. Solution Engineer to learn how DataOps teams orchestrate their end-to-end data pipelines with a platform approach to managing automation. Key Learnings: - Discover how to orchestrate data pipelines across a hybrid IT environment (on-prem and cloud) - Find out how DataOps teams are empowered with event-based triggers for real-time data flow - See examples of reports, dashboards, and proactive alerts designed to help you reliably keep data flowing through your business — with the observability you require - Discover how to replace clunky legacy approaches to streaming data in a multi-cloud environment - See what’s possible with the Stonebranch Universal Automation Center (UAC)

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DATAVERSITY

Every business today wants to leverage data to drive strategic initiatives with machine learning, data science and analytics — but runs into challenges from siloed teams, proprietary technologies and unreliable data. That’s why enterprises are turning to the lakehouse because it offers a single platform to unify all your data, analytics and AI workloads. Join our How to Build a Lakehouse technical training, where we’ll explore how to use Apache SparkTM, Delta Lake, and other open source technologies to build a better lakehouse. This virtual session will include concepts, architectures and demos. Here’s what you’ll learn in this 2-hour session: How Delta Lake combines the best of data warehouses and data lakes for improved data reliability, performance and security How to use Apache Spark and Delta Lake to perform ETL processing, manage late-arriving data, and repair corrupted data directly on your lakehouse

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Francesco Furiani - Marketing is a serious business, moreover tracking and monetizing the campaign that allows your marketing to flourish is very important: our tool allows anyone to monitor, compare and optimize all those campaigns (delivered via links) in one place and to deliver insights about who's using those links. Making this infrastructure, making it works, deliver results in real-time (when necessary) and keep everyone happy from the customer to the CFO will be the point of this talk, from the design to the final result with an eye on the costs/risks/benefits of having everything in the cloud.

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The Briefing Room with Barry Devlin and WhereScape Live Webcast on June 10, 2014 Watch the archive: https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=5230c31ab287778c73b56002bc2c51a The data warehouse is intended to support analysis by making the right data available to the right people in a timely fashion. But conditions change all the time, and when data doesn’t keep up with the business, analysts quickly turn to workarounds. This leads to ungoverned and largely un-managed side projects, which trade short-term wins for long-term trouble. One way to keep everyone happy is by creating an integrated environment that pulls data from all sources, and is capable of automating both the model development and delivery of analyst-ready data. Register for this episode of The Briefing Room to hear data warehousing pioneer and Analyst Barry Devlin as he explains the critical components of a successful data warehouse environment, and how traditional approaches must be augmented to keep up with the times. He’ll be briefed by WhereScape CEO Michael Whitehead, who will showcase his company’s data warehousing automation solutions. He’ll discuss how a fast, well-managed and automated infrastructure is the key to empowering faster, smarter, repeatable decision making. Visit InsideAnlaysis.com for more information.

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It is a fascinating, explosive time for enterprise analytics. It is from the position of analytics leadership that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics. The coming years will be full of big changes in enterprise analytics and Data Architecture. William will kick off the fourth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.

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DATAVERSITY

Watch full webinar here: https://bit.ly/2TF7ATo ติดสปีดการวิเคราะห์ข้อมูลด้วยตัวเองแบบรวดเร็วแม่นยำด้วย Data Virtualization และ Data Visualisation องค์กรชั้นนำกำลังขยับตัวไปสู่การวิเคราะห์ข้อมูลทางธุรกิจด้วยตัวเอง เพราะผู้ใช้งานต้องการการเข้าถึงข้อมูลแบบทันทีเพื่อเห็นภาพแบบองค์รวมและหลากหลายมิติโดยไม่ต้องคำนึงถึง ตำแหน่งและ แหล่งที่มา หรือชนิดของข้อมูลสำหรับการตัดสินใจครั้งสำคัญ Data Virtualization (การทำให้เห็นข้อมูลแบบเสมือนจริง) และ Data Visualisation (การทำให้เห็นข้อมูลเป็นภาพ)ทำงานด้วยกันผ่านชั้นข้อมูลเชิงความหมายที่เป็นรูปแบบสากล Webinar นี้คุณจะได้รู้วิธีว่าเราจะสามารถค้นพบข้อมูลมาวิเคราะห์ด้วยตัวเองอย่างไรและยกระดับประสิทธิภาพการทำรายงานและแดชบอร์ดของคุณได้อย่างไร ใน Webinar นี้ คุณจะได้เรียนรู้เรื่อง อุปสรรคและความท้าทายที่ผู้ใช้งานในองค์กรธุรกิจต้องเผชิญ Data Virtualization ทำให้คุณสามารถวิเคราะห์ข้อมูลได้ด้วยตัวเองได้อย่างไร กรณีศึกษาและบทเรียนจากความสำเร็จของลูกค้า สรุป Tableau Highlight Features

Accelerate Self-Service Analytics with Virtualization and Visualisation (Thai)

Denodo

Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad. Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad. Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad. Enroll in our Azure Data Engineering Course in Hyderabad to gain in-depth knowledge of Microsoft Azure's powerful data processing capabilities. Learn essential skills such as data ingestion, storage, and analytics using Azure services. Our hands-on training, led by industry experts, will equip you with the expertise needed to design and implement robust data solutions. Prepare for a successful career in data engineering with our specialized course in the heart of Hyderabad.

Azure Data Engineering.pdf

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"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"?

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