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Learn about DataOps, a methodology that encompasses modern integration technologies, the processes that transform data from raw to ready, ...
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Key Tenets of DataOps
Data Pipelines
Conclusion
Data operations or DataOps brings speed, agility, and compliance to a company's data processes. The DataOps approach involves collaborative ...
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How to get the most out of DataOps?
Five capabilities to look for when selecting a DataOps solution
Seamless Data Integration & Interoperability
Examples of DataOps in use
DataOps Demystified in 60 Seconds by Bernard Marr Key Points: Definition: DataOps is to data what DevOps is to development - it's ...
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In this video, you will understand what DataOps is, the key three components of DataOps, DataOps paradigm, types of people involved, ...
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Comments6 · 3 Must-Know Trends for Data Engineers | DataOps · 5 Steps to Optimize your dbt Implementation · 5 Of The Most Dangerous Jobs In The ...
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Agenda
Background
Bob the Data Analyst
Complex Data Lineage
Data Quality Issues
Make It Reproducible
Fourth Principle Is Monitor Quality and Performance
Avoid Burnout
Burnout
Resources
The State of DataOps presented by Wayne Eckerson, President @ Eckerson Group and Kunal Agarwal, Co-Founder & CEO at Unravel Data a leader in ...
YouTube-Unravel Data
Intro
How to unblock these challenges?
Artisan to Industrial Evolution
TQM (Total Quality Management)
DataOps lifecycle
DataOps Operations
Self-sufficient DataOps teams
What are our major bottlenecks?
Q&A: How does version control play a role in DataOps?
Andy Palmer, Co-Founder and CEO at Tamr, uncovers the purpose and future of DataOps. https://www.tamr.com #data #dataops #tamr #bigdata.
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Why is DataOps important?
DataOps history
DataOps is about people, processes, and human behaviors
Building the DataOps ecosystem
Benefits of an open, loosely coupled ecosystem
Automation
Why embrace DataOps?
DevOps meets DataOps: Oracle's End-to-End OpenTelemetry Observability Across Apps, Kubernetes, and Database In this session, we'll show you ...
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Oracle Database Operator
Supporting Logs
Metrics Logs and Tracing
Agents
Api for the Tracing Agent in Jdbc
Client Side Trace
Deep Observability
Proactive Monitoring
Observability of ( _ _ ) Stacks
When you think about a data team, what comes to mind? Maybe you think about a single group of developers along with some QA support.
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Integration
Collaboration
Attend this session to learn how you can leverage #DataOps to deliver value faster by establishing predictable delivery and management of ...
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What Is Data Ops
Challenges
Pipeline Failures
Bmcc's Value in Pipeline Optimization
DataOps is an emerging methodology for building and automating data pipelines. Drawing from DevOps and agile approaches to software ...
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Opening Remarks
What is DataOps?
What is orchestration?
Scheduling Data Pipelines
Where to start?
Componentization
Evaluating DataOps
DataOps Platform Overview
How do you recommend addressing the people component of DataOps?
Outro
In this video we take a look at an emerging product called DataOps - dataops.live. DataOps aims to improve delivery whilst maintaining ...
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Legacy Infrastructure
Orchestration Element
Data Drops
Highlights
Reducing the Minimal Viable Product Time
Master and Snowflake Program
Modules
DataOps has grown because of the need to support execution at scale in the data management space. During this session Vijay Kiran, ...
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Core Principles
Implement the Best Practices for the Development
Continuous Integration
Cross-Functional Teams
Implement Best Practices for Development
Unit Testing
Artifacts Management
"DataOps CTO Guy Adams is joined by a team of DataOps data engineers to demonstrate the power of the DataOps.live, a platform that helps ...
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Luke Crumley DataOps and CloudOps Engineer
Aleksandra Shumkoska DataOps and CloudOps Engineer
Abhinav Kumar DataOps and CloudOps Engineer
DataOps.live describes how their platform based on the #TrueDataOps Philosophy aligns with Data Governance principals.
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Keith Belanger
How Does Data Ops in General Play a Role in Data Governance
Automation and Orchestration
Power BI has revolutionized the industry by accelerating our ability to deliver Data Analytics solutions. But how do we ensure the code we ...
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Make it reproducible
Sync your onedrive with with power bi
Detect any abnormalities in your data
Build the end-to-end orchestration
Building dashboards and reports
Deploying your power bi reports to production
Start monitoring your workspaces
Reading the json
DataOps for Snowflake is ONE platform for 100% of your DataOps lifecycle to enable agility and responsiveness, with no compromise on data ...
Why can't data teams make changes in minutes and hours like our DevOps teams?
Data Platforms are Complicated
What if we could bring the speed and agility of DevOps and CI/CD to data platforms?
Benefits of DataOps for Snowflake
Edureka DevOps Training: https://www.edureka.co/devops-certification-training/ This Edureka "What is DataOps" gives you a complete overview ...
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Introduction
Benefits of DataOps
DataOps Platform
DataOps Architecture
DevOps vs DataOps
Implementing DataOps
Who is a DataOps Engineer?
Case Study
You've implemented a new cloud data platform using Snowflake. You're eager to gain the benefits of cloud computing and work in a more agile, ...
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Where did DataOps come from?
DataOps Scenario
Are tests also run in production?
Feature Branch Pipeline
DataOps Pipeline Demo
Imperative vs Decorative Approach
Audience Q&A
Schedule jobs
Closing Remarks
DataOps is a framework that lifts best practices from DevOps in the software development world and applies it to delivering data in an ...
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International Bank DataOps Impact
Data pipelines are the bottleneck to delivering data to users
DataOps requires Automation and Multi-Cloud Architecture
Why IBM: A modern architecture for today and the future
Turning Bottlenecks into Opportunities
Introducing the "DataOps Center of Excellence" Team