SLC Snowflake User Group - Mar 12, 2020
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Vivint Smart Home's journey with Snowflake and migrating from SQL Server. We describe how we have setup snowflake from a people, process, and technology perspective.
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SQL Analytics Powering Telemetry Analysis at Comcast
Comcast is one of the leading providers of communications, entertainment, and cable products and services. At the heart of it is Comcast RDK providing the backbone of telemetry to the industry. RDK (Reference Design Kit) is pre-bundled opensource firmware for a complete home platform covering video, broadband and IoT devices. RDK team at Comcast analyzes petabytes of data, collected every 15 minutes from 70 million devices (video and broadband and IoT devices) installed in customer homes. They run ETL and aggregation pipelines and publish analytical dashboards on a daily basis to reduce customer calls and firmware rollout. The analysis is also used to calculate WIFI happiness index which is a critical KPI for Comcast customer experience.
In addition to this, RDK team also does release tracking by analyzing the RDK firmware quality. SQL Analytics allows customers to operate a lakehouse architecture that provides data warehousing performance at data lake economics for up to 4x better price/performance for SQL workloads than traditional cloud data warehouses.
We present the results of the “Test and Learn” with SQL Analytics and the delta engine that we worked in partnership with the Databricks team. We present a quick demo introducing the SQL native interface, the challenges we faced with migration, The results of the execution and our journey of productionizing this at scale.
KoprowskiT_SQLRelay2014#9_London_FromPlanToBackupToCloud
Microsoft released SQL Azure more than two years ago - that's enough time for testing (I hope!). So, are you ready to move your data to the Cloud? If you’re considering a business (i.e. a production environment) in the Cloud, you need to think about methods for backing up your data, a backup plan for your data and, eventually, restoring with Red Gate Cloud Services. In this session, you’ll see the differences, functionality, restrictions, and opportunities in SQL Azure and On-Premise SQL Server 2008/2008 R2/2012. We’ll consider topics such as how to be prepared for backup and restore, and which parts of a cloud environment are most important: keys, triggers, indexes, prices, security, service level agreements, etc.
Data Culture Series - Keynote - 3rd Dec
Big data. Small data. All data. You have access to an ever-expanding volume of data inside the walls of your business and out across the web. The potential in data is endless – from predicting election results to preventing the spread of epidemics. But how can you use it to your advantage to help move your business forward?
Drive a Data Culture within your organisation
Keynote include Ric Howe & Anthony Saxby
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartori
The document discusses considerations for migrating databases to Microsoft Azure SQL Database. It covers cloud options like Infrastructure as a Service (IaaS) using SQL Server on Azure VMs and Platform as a Service (PaaS) options like Azure SQL Database. It also discusses analyzing database compatibility, different migration methods like using BACPAC files or the Data Migration Assistant, and ways to optimize the migration process like monitoring tempdb usage.
Tableau & MongoDB: Visual Analytics at the Speed of Thought
This document discusses how Tableau and MongoDB can work together for visual analytics of big data. It describes how MongoDB is a NoSQL database that can handle unstructured and semi-structured data like JSON, and how Tableau allows users to connect to MongoDB through an ODBC driver and visualize the data without needing to write code. The document outlines scenarios where big data comes from human, machine, and process sources and how the combination of Tableau and MongoDB's schema-on-read approach reduces the need for ETL. It also previews demos of connecting Tableau to MongoDB using both the ODBC driver and a PostgreSQL interface.
Modernizing Global Shared Data Analytics Platform and our Alluxio Journey
Data Orchestration Summit 2020 organized by Alluxio
https://www.alluxio.io/data-orchestration-summit-2020/
Modernizing Global Shared Data Analytics Platform and our Alluxio Journey
Sandipan Chakraborty, Director of Engineering (Rakuten)
About Alluxio: alluxio.io
Engage with the open source community on slack: alluxio.io/slack
Refactoring your EDW with Mobile Analytics Products
The document discusses refactoring an enterprise data warehouse (EDW) at China Construction Bank (CCB) to leverage mobile analytics and big data. CCB has a large existing EDW infrastructure handling over 1PB of core data and 4TB of incremental data daily. They have transformed their EDW over time, adding a Hadoop platform and migrating some data and queries. Kyligence products help accelerate queries and enable self-service analytics on the large data volumes.
It ready dw_day3_rev00
The document provides an agenda for a 3-day training on data warehousing and business intelligence using Microsoft SQL Server 2005. Day 3 focuses on SQL Server Integration Services (SSIS), including an introduction to SSIS, workshops and exercises on SSIS and SQL Server Analysis Services (SSAS). It also discusses how to create SSIS packages to extract, transform and load data.
SQLCAT: Tier-1 BI in the World of Big Data
This document summarizes a presentation on tier-1 business intelligence (BI) in the world of big data. The presentation will cover Microsoft's BI capabilities at large scales, big data workloads from Yahoo and investment banks, Hadoop and the MapReduce framework, and extracting data out of big data systems into BI tools. It also shares a case study on Yahoo's advertising analytics platform that processes billions of rows daily from terabytes of data.
Add Redis to Postgres to Make Your Microservices Go Boom!
Slides for talk delivered at PostgresOpen 2018 in San Francisco https://postgresql.us/events/pgopen2018/schedule/session/538-add-redis-to-postgres-to-make-your-microservice-go-boom/
Cloud-native Semantic Layer on Data Lake
With larger volume and more real-time data stored in data lake, it becomes more complex to manage these data and serve analytics and applications. With different service interfaces, data caliber, performance bias on different scenarios, the business users begin to suffer low confidence on quality and efficiency to get insight from data.
Oow2016 review-db-dev-bigdata-BI
Oracle OpenWorld 2016 focused on several key themes:
1. A shift away from a single, central Oracle database and toward distributed architectures like PDBs, sharding, Hadoop, and machine learning.
2. Adopting open source technologies and industry trends like Node.js, Docker, microservices, and Python.
3. Advancing Oracle's cloud strategy through migration tools, cloud@customer, and subscription models while improving the user experience of SaaS applications.
Oracle OpenWorld 2016 Review - Focus on Data, BigData, Streaming Data, Machin...
One key area of Oracle OpenWorld 2016 was data in various shapes. Big Data, streaming data and traditional transactional data. The power of SQL to access and unleash all data - even data in NoSQL databases. The advent of the citizen data scientist. Streaming data analysis in real time on vast and fast and vast data, data discovery. And the new Oracle Database 12cR2 release. Forms, APEX, SQL and PL/SQL.
Azure Synapse Analytics Overview (r2)
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.
Myth Busters II: BI Tools and Data Virtualization are Interchangeable
Watch Here: https://bit.ly/2NcqU6F
We take on the 2nd myth about data virtualization and it’s one that suggests a BI tool can substitute a data virtualization software.
You might be thinking: If I can have multi-source queries and define a logical model in my reporting tool, why would I need a data virtualization software?
Reporting tools, no doubt important and necessary, focus on the visualization of data and it’s presentation to the business user. Data virtualization is a governed data access layer designed to connect to and provide transparency of all enterprise data.
Yet the myth suggests that these technologies are interchangeable. So we’re going to take it on!
Watch this webinar as we compare and contrast BI tools and data virtualization to draw a final conclusion.
AMIS Oracle OpenWorld 2013 Review Part 1 - Intro Overview Innovation, Hardwar...
AMIS Oracle OpenWorld 2013 Review Part 1 - Intro Overview Innovation, Hardwar...Getting value from IoT, Integration and Data Analytics
The document provides an agenda and overview of announcements from Oracle OpenWorld 2013. Key announcements include the Oracle Database In Memory option, Sparc M6-32 server, Backup Logging and Recovery Appliance, expanded cloud services, and new capabilities for big data and JSON. Oracle aims to lead in areas around big data, in-memory computing, and cloud services and hopes to ease customers' transition to mobile, cloud, and big data technologies.Presto @ Treasure Data - Presto Meetup Boston 2015
Treasure Data simplifies event analytics for the complex digital
world. Our customers send us 1,000,000 events per second and issue 30,000+ Presto queries everyday to understand their customers better. One of the challenges is designing a cloud database with zero downtime to support a global customer base. We have achieved this goal by developing several open-source technologies; Fluentd and Embulk enable seamless log collection from stream/batch sources, and with MessagePack we can provide an extensible columnar store that accommodates future schema changes. Finally, Presto allows us to serve a wide variety of data processing our customers perform on our service. In this talk, I will present an overview of our system, and how our customers keep using Presto while collecting and extending their data set.
Ensuring Quality in Data Lakes (D&D Meetup Feb 22)
The document discusses improving data quality in a data lake. It describes three levels (L1-L3) of data lake maturity:
L1 involves storing data in an object store in a basic format like CSV files. This provides good performance, cost efficiency, and developer experience.
L2 adds optimized table formats like Delta Lake, Hudi and Iceberg that maintain metadata and transaction logs to enable features like schema enforcement, data versioning and isolation.
L3 adds data version control systems like lakeFS that extend the object store with Git-like source control operations. This allows instantly reverting bad data, developing data in isolation, and simplifying data reproducibility. LakeFS was demonstrated as an example solution
Free Training: How to Build a Lakehouse
Doug Bateman, a principal data engineering instructor at Databricks, presented on how to build a Lakehouse architecture. He began by introducing himself and his background. He then discussed the goals of describing key Lakehouse features, explaining how Delta Lake enables it, and developing a sample Lakehouse using Databricks. The key aspects of a Lakehouse are that it supports diverse data types and workloads while enabling using BI tools directly on source data. Delta Lake provides reliability, consistency, and performance through its ACID transactions, automatic file consolidation, and integration with Spark. Bateman concluded with a demo of creating a Lakehouse.
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SQL Analytics Powering Telemetry Analysis at Comcast
SQL Analytics Powering Telemetry Analysis at Comcast
KoprowskiT_SQLRelay2014#9_London_FromPlanToBackupToCloud
KoprowskiT_SQLRelay2014#9_London_FromPlanToBackupToCloud
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartori
CCI2017 - Considerations for Migrating Databases to Azure - Gianluca Sartori
Tableau & MongoDB: Visual Analytics at the Speed of Thought
Tableau & MongoDB: Visual Analytics at the Speed of Thought
Modernizing Global Shared Data Analytics Platform and our Alluxio Journey
Modernizing Global Shared Data Analytics Platform and our Alluxio Journey
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Refactoring your EDW with Mobile Analytics Products
Add Redis to Postgres to Make Your Microservices Go Boom!
Add Redis to Postgres to Make Your Microservices Go Boom!
Oracle OpenWorld 2016 Review - Focus on Data, BigData, Streaming Data, Machin...
Oracle OpenWorld 2016 Review - Focus on Data, BigData, Streaming Data, Machin...
Myth Busters II: BI Tools and Data Virtualization are Interchangeable
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AMIS Oracle OpenWorld 2013 Review Part 1 - Intro Overview Innovation, Hardwar...
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Presto @ Treasure Data - Presto Meetup Boston 2015
Presto @ Treasure Data - Presto Meetup Boston 2015
Ensuring Quality in Data Lakes (D&D Meetup Feb 22)
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Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
Dmitrii Kamaev, PhD
Senior Product Owner - QIAGEN
Mutation Testing for Task-Oriented Chatbots
Conversational agents, or chatbots, are increasingly used to access all sorts of services using natural language. While open-domain chatbots - like ChatGPT - can converse on any topic, task-oriented chatbots - the focus of this paper - are designed for specific tasks, like booking a flight, obtaining customer support, or setting an appointment. Like any other software, task-oriented chatbots need to be properly tested, usually by defining and executing test scenarios (i.e., sequences of user-chatbot interactions). However, there is currently a lack of methods to quantify the completeness and strength of such test scenarios, which can lead to low-quality tests, and hence to buggy chatbots.
To fill this gap, we propose adapting mutation testing (MuT) for task-oriented chatbots. To this end, we introduce a set of mutation operators that emulate faults in chatbot designs, an architecture that enables MuT on chatbots built using heterogeneous technologies, and a practical realisation as an Eclipse plugin. Moreover, we evaluate the applicability, effectiveness and efficiency of our approach on open-source chatbots, with promising results.
Dandelion Hashtable: beyond billion requests per second on a commodity server
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
Apps Break Data
How information systems are built or acquired puts information, which is what they should be about, in a secondary place. Our language adapted accordingly, and we no longer talk about information systems but applications. Applications evolved in a way to break data into diverse fragments, tightly coupled with applications and expensive to integrate. The result is technical debt, which is re-paid by taking even bigger "loans", resulting in an ever-increasing technical debt. Software engineering and procurement practices work in sync with market forces to maintain this trend. This talk demonstrates how natural this situation is. The question is: can something be done to reverse the trend?
LF Energy Webinar: Carbon Data Specifications: Mechanisms to Improve Data Acc...
This LF Energy webinar took place June 20, 2024. It featured:
-Alex Thornton, LF Energy
-Hallie Cramer, Google
-Daniel Roesler, UtilityAPI
-Henry Richardson, WattTime
In response to the urgency and scale required to effectively address climate change, open source solutions offer significant potential for driving innovation and progress. Currently, there is a growing demand for standardization and interoperability in energy data and modeling. Open source standards and specifications within the energy sector can also alleviate challenges associated with data fragmentation, transparency, and accessibility. At the same time, it is crucial to consider privacy and security concerns throughout the development of open source platforms.
This webinar will delve into the motivations behind establishing LF Energy’s Carbon Data Specification Consortium. It will provide an overview of the draft specifications and the ongoing progress made by the respective working groups.
Three primary specifications will be discussed:
-Discovery and client registration, emphasizing transparent processes and secure and private access
-Customer data, centering around customer tariffs, bills, energy usage, and full consumption disclosure
-Power systems data, focusing on grid data, inclusive of transmission and distribution networks, generation, intergrid power flows, and market settlement data
Essentials of Automations: Exploring Attributes & Automation Parameters
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
Harnessing the Power of NLP and Knowledge Graphs for Opioid Research
Gursev Pirge, PhD
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Northern Engraving | Nameplate Manufacturing Process - 2024
Manufacturing custom quality metal nameplates and badges involves several standard operations. Processes include sheet prep, lithography, screening, coating, punch press and inspection. All decoration is completed in the flat sheet with adhesive and tooling operations following. The possibilities for creating unique durable nameplates are endless. How will you create your brand identity? We can help!
JavaLand 2024: Application Development Green Masterplan
My presentation slides I used at JavaLand 2024
Leveraging the Graph for Clinical Trials and Standards
Katja Glaß
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Marius Conjeaud
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Connector Corner: Seamlessly power UiPath Apps, GenAI with prebuilt connectors
Join us to learn how UiPath Apps can directly and easily interact with prebuilt connectors via Integration Service--including Salesforce, ServiceNow, Open GenAI, and more.
The best part is you can achieve this without building a custom workflow! Say goodbye to the hassle of using separate automations to call APIs. By seamlessly integrating within App Studio, you can now easily streamline your workflow, while gaining direct access to our Connector Catalog of popular applications.
We’ll discuss and demo the benefits of UiPath Apps and connectors including:
Creating a compelling user experience for any software, without the limitations of APIs.
Accelerating the app creation process, saving time and effort
Enjoying high-performance CRUD (create, read, update, delete) operations, for
seamless data management.
Speakers:
Russell Alfeche, Technology Leader, RPA at qBotic and UiPath MVP
Charlie Greenberg, host
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...
“Temporal Event Neural Networks: A More Efficient Alternative to the Transfor...Edge AI and Vision Alliance
For the full video of this presentation, please visit: https://www.edge-ai-vision.com/2024/06/temporal-event-neural-networks-a-more-efficient-alternative-to-the-transformer-a-presentation-from-brainchip/
Chris Jones, Director of Product Management at BrainChip , presents the “Temporal Event Neural Networks: A More Efficient Alternative to the Transformer” tutorial at the May 2024 Embedded Vision Summit.
The expansion of AI services necessitates enhanced computational capabilities on edge devices. Temporal Event Neural Networks (TENNs), developed by BrainChip, represent a novel and highly efficient state-space network. TENNs demonstrate exceptional proficiency in handling multi-dimensional streaming data, facilitating advancements in object detection, action recognition, speech enhancement and language model/sequence generation. Through the utilization of polynomial-based continuous convolutions, TENNs streamline models, expedite training processes and significantly diminish memory requirements, achieving notable reductions of up to 50x in parameters and 5,000x in energy consumption compared to prevailing methodologies like transformers.
Integration with BrainChip’s Akida neuromorphic hardware IP further enhances TENNs’ capabilities, enabling the realization of highly capable, portable and passively cooled edge devices. This presentation delves into the technical innovations underlying TENNs, presents real-world benchmarks, and elucidates how this cutting-edge approach is positioned to revolutionize edge AI across diverse applications.ScyllaDB Tablets: Rethinking Replication
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
"Scaling RAG Applications to serve millions of users", Kevin Goedecke
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
AppSec PNW: Android and iOS Application Security with MobSF
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
Must Know Postgres Extension for DBA and Developer during Migration
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
Main news related to the CCS TSI 2023 (2023/1695)
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
"What does it really mean for your system to be available, or how to define w...
We will talk about system monitoring from a few different angles. We will start by covering the basics, then discuss SLOs, how to define them, and why understanding the business well is crucial for success in this exercise.
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Biomedical Knowledge Graphs for Data Scientists and Bioinformaticians
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Nordic Marketo Engage User Group_June 13_ 2024.pptx
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"What does it really mean for your system to be available, or how to define w...
SLC Snowflake User Group - Mar 12, 2020
- 1. 3.12.2020 SLC Snowflake User Group
- 2. WELCOME • 2:00 – 2:30: Food, Network • 2:30 – 3:00: Introductions • 3:00 – 3:30: Vivint’s Snowflake Journey • 3:30 – 4:00: Q&A, Discussion WiFi: vivint.guest SLC Snowflake User Group 3.12.2020
- 4. 4 DATA LANDSCAPE - BEFORESourceData Prod 1 Prod 2 ETLData Warehouse Data Visualization Prod 1 (Windows, SSIS)
- 5. CHALLENGES 5
- 6. 6NDEXESI
- 7. 7
- 8. 8
- 9. CHALLENGES 9 Performance Tuning, Tuning, Tuning Constant Battle Scalability I want my data warehouse to grow! Hardware upgrades require migration Performance depreciation is real! Resource Contention ETL processes vs Reports vs Analysts Isolation is expensive
- 10. 10 ETL Prod1 (Linux, Python) ETL Dev1 (Linux, Python) SourceData Prod 1 (Windows, SSIS) Staging 1 (Windows, SSIS) ETLData Warehouse Data Visualization New NewNew Reporting Web Portal (Linux, Webserver) New New
- 11. SETUP People • Data Engineering: pipelines, data lake • Data Warehouse Engineering: ETL, Data Modeling, Data Warehouse • Data Analysts: Department specific Process • Development: Dev DB per engineer • Security & Compliance: Roles, Sensitive Data, SOX • Self-Service & Governance: Data Store + Sandbox, Enterprise Data Council Technology • Snowflake: 8 warehouses, 54 TB • Pipelines: Python, FiveTran • ETL: SSIS + Azure DevOps for Continuous Deployment • Dashboards: Tableau & Domo
- 12. 54.0 TBs (compressed) 8 Warehouses 4 Data Shares 6,653 PROD Tables 229 PROD Schemas 3,339 PROD Views 334 Users 89 Roles
- 13. ETL1 – Primary WH for Data Eng. pipelines ETL_DEV –Data Eng. Pipelines development WH ETL_XS – Primary WH for ETL quick running jobs ETL_S – WH for ETL jobs that require more processing power ETL_M – WH for heavy ETL jobsANALYTICS – Dedicated WH for analysts use NIS – NIS engineering/analyst projects (partner portal) PRESENTATION – Dedicated WH for curated data sources Warehouses