Amazon Redshift รฉ um serviรงo gerenciado que lhe dรก um Data Warehouse, pronto para usar. Vocรช se preocupa com carregar dados e utilizรก-lo. Os detalhes de infraestrutura, servidores, replicaรงรฃo, backup sรฃo administrados pela AWS.
Whatโs New in the Upcoming Apache Spark 3.0Databricks
ย
Learn about the latest developments in the open-source community with Apache Spark 3.0 and DBR 7.0The upcoming Apache Sparkโข 3.0 release brings new capabilities and features to the Spark ecosystem. In this online tech talk from Databricks, we will walk through updates in the Apache Spark 3.0.0-preview2 release as part of our new Databricks Runtime 7.0 Beta, which is now available.
Best Practices for Building a Data Lake with Amazon S3 - August 2016 Monthly ...Amazon Web Services
ย
Uncovering new, valuable insights from big data requires organizations to collect, store, and analyze increasing volumes of data from multiple, often disparate sources at disparate points in time. This makes it difficult to handle big data with data warehouses or relational database management systems alone. A Data Lake allows you to store massive amounts of data in its original form, without the need to enforce a predefined schema, enabling a far more agile and flexible architecture, which makes it easier to gain new types of analytical insights from your data.
Learning Objectives:
โข Introduce key architectural concepts to build a Data Lake using Amazon S3 as the storage layer
โข Explore storage options and best practices to build your Data Lake on AWS
โข Learn how AWS can help enable a Data Lake architecture
โข Understand some of the key architectural considerations when building a Data Lake
โข Hear some important Data Lake implementation considerations when using Amazon S3 as your Data Lake
Hadoop 3.0 has been years in the making, and now it's finally arriving. Andrew Wang and Daniel Templeton offer an overview of new features, including HDFS erasure coding, YARN Timeline Service v2, YARN federation, and much more, and discuss current release management status and community testing efforts dedicated to making Hadoop 3.0 the best Hadoop major release yet.
(BDT322) How Redfin & Twitter Leverage Amazon S3 For Big DataAmazon Web Services
ย
Analyzing large data sets requires significant compute and storage capacity that can vary in size based on the amount of input data and the analysis required. This characteristic of big data workloads is ideally suited to the pay-as-you-go cloud model, where applications can easily scale up and down based on demand. Learn how Amazon S3 can help scale your big data platform. Hear from Redfin and Twitter about how they build their big data platforms on AWS and how they use S3 as an integral piece of their big data platforms.
Meta/Facebook's database serving social workloads is running on top of MyRocks (MySQL on RocksDB). This means our performance and reliability depends a lot on RocksDB. Not just MyRocks, but also we have other important systems running on top of RocksDB. We have learned many lessons from operating and debugging RocksDB at scale.
In this session, we will offer an overview of RocksDB, key differences from InnoDB, and share a few interesting lessons learned from production.
Amazon Redshift รฉ um serviรงo gerenciado que lhe dรก um Data Warehouse, pronto para usar. Vocรช se preocupa com carregar dados e utilizรก-lo. Os detalhes de infraestrutura, servidores, replicaรงรฃo, backup sรฃo administrados pela AWS.
Whatโs New in the Upcoming Apache Spark 3.0Databricks
ย
Learn about the latest developments in the open-source community with Apache Spark 3.0 and DBR 7.0The upcoming Apache Sparkโข 3.0 release brings new capabilities and features to the Spark ecosystem. In this online tech talk from Databricks, we will walk through updates in the Apache Spark 3.0.0-preview2 release as part of our new Databricks Runtime 7.0 Beta, which is now available.
Best Practices for Building a Data Lake with Amazon S3 - August 2016 Monthly ...Amazon Web Services
ย
Uncovering new, valuable insights from big data requires organizations to collect, store, and analyze increasing volumes of data from multiple, often disparate sources at disparate points in time. This makes it difficult to handle big data with data warehouses or relational database management systems alone. A Data Lake allows you to store massive amounts of data in its original form, without the need to enforce a predefined schema, enabling a far more agile and flexible architecture, which makes it easier to gain new types of analytical insights from your data.
Learning Objectives:
โข Introduce key architectural concepts to build a Data Lake using Amazon S3 as the storage layer
โข Explore storage options and best practices to build your Data Lake on AWS
โข Learn how AWS can help enable a Data Lake architecture
โข Understand some of the key architectural considerations when building a Data Lake
โข Hear some important Data Lake implementation considerations when using Amazon S3 as your Data Lake
Hadoop 3.0 has been years in the making, and now it's finally arriving. Andrew Wang and Daniel Templeton offer an overview of new features, including HDFS erasure coding, YARN Timeline Service v2, YARN federation, and much more, and discuss current release management status and community testing efforts dedicated to making Hadoop 3.0 the best Hadoop major release yet.
(BDT322) How Redfin & Twitter Leverage Amazon S3 For Big DataAmazon Web Services
ย
Analyzing large data sets requires significant compute and storage capacity that can vary in size based on the amount of input data and the analysis required. This characteristic of big data workloads is ideally suited to the pay-as-you-go cloud model, where applications can easily scale up and down based on demand. Learn how Amazon S3 can help scale your big data platform. Hear from Redfin and Twitter about how they build their big data platforms on AWS and how they use S3 as an integral piece of their big data platforms.
Meta/Facebook's database serving social workloads is running on top of MyRocks (MySQL on RocksDB). This means our performance and reliability depends a lot on RocksDB. Not just MyRocks, but also we have other important systems running on top of RocksDB. We have learned many lessons from operating and debugging RocksDB at scale.
In this session, we will offer an overview of RocksDB, key differences from InnoDB, and share a few interesting lessons learned from production.
NoSQL databases get a lot of press coverage, but there seems to be a lot of confusion surrounding them, as in which situations they work better than a Relational Database, and how to choose one over another. This talk will give an overview of the NoSQL landscape and a classification for the different architectural categories, clarifying the base concepts and the terminology, and will provide a comparison of the features, the strengths and the drawbacks of the most popular projects (CouchDB, MongoDB, Riak, Redis, Membase, Neo4j, Cassandra, HBase, Hypertable).
026 Neo4j Data Loading (ETL_ELT) Best Practices - NODES2022 AMERICAS Advanced...Neo4j
ย
What patterns are most appropriate for building ETLs using Neo4j? In this session, we share how we built the Google Cloud DataFlow flex template using the Neo4j Java API. You can then apply the same approach to building read and write operators in any framework, including AWS Lambda and Google Cloud Functions.
The Future of Data Science and Machine Learning at Scale: A Look at MLflow, D...Databricks
ย
Many had dubbed 2020 as the decade of data. This is indeed an era of data zeitgeist.
From code-centric software development 1.0, we are entering software development 2.0, a data-centric and data-driven approach, where data plays a central theme in our everyday lives.
As the volume and variety of data garnered from myriad data sources continue to grow at an astronomical scale and as cloud computing offers cheap computing and data storage resources at scale, the data platforms have to match in their abilities to process, analyze, and visualize at scale and speed and with ease โ this involves data paradigm shifts in processing and storing and in providing programming frameworks to developers to access and work with these data platforms.
In this talk, we will survey some emerging technologies that address the challenges of data at scale, how these tools help data scientists and machine learning developers with their data tasks, why they scale, and how they facilitate the future data scientists to start quickly.
In particular, we will examine in detail two open-source tools MLflow (for machine learning life cycle development) and Delta Lake (for reliable storage for structured and unstructured data).
Other emerging tools such as Koalas help data scientists to do exploratory data analysis at scale in a language and framework they are familiar with as well as emerging data + AI trends in 2021.
You will understand the challenges of machine learning model development at scale, why you need reliable and scalable storage, and what other open source tools are at your disposal to do data science and machine learning at scale.
Cosco: An Efficient Facebook-Scale Shuffle ServiceDatabricks
ย
Cosco is an efficient shuffle-as-a-service that powers Spark (and Hive) jobs at Facebook warehouse scale. It is implemented as a scalable, reliable and maintainable distributed system. Cosco is based on the idea of partial in-memory aggregation across a shared pool of distributed memory. This provides vastly improved efficiency in disk usage compared to Spark's built-in shuffle. Long term, we believe the Cosco architecture will be key to efficiently supporting jobs at ever larger scale. In this talk we'll take a deep dive into the Cosco architecture and describe how it's deployed at Facebook. We will then describe how it's integrated to run shuffle for Spark, and contrast it with Spark's built-in sort-based shuffle mechanism and SOS (presented at Spark+AI Summit 2018).
Using all of the high availability options in MariaDBMariaDB plc
ย
MariaDB provides a number of high availability options, including replication with automatic failover and multi-master clustering. In this session Wagner Bianchi, Principal Remote DBA, provides a comprehensive overview of the high availability features in MariaDB, highlights their impact on consistency and performance, discusses advanced failover strategies and introduces new features such as casual reads and transparent connection failover.
Differentiate Big Data vs Data Warehouse use cases for a cloud solutionJames Serra
ย
It can be quite challenging keeping up with the frequent updates to the Microsoft products and understanding all their use cases and how all the products fit together. ย In this session we will differentiate the use cases for each of the Microsoft services, explaining and demonstrating what is good and what isn't, in order for you to position, design and deliver the proper adoption use cases for each with your customers. ย We will cover a wide range of products such as Databricks, SQL Data Warehouse, HDInsight, Azure Data Lake Analytics, Azure Data Lake Store, Blob storage, and AAS ย as well as high-level concepts such as when to use a data lake.ย We will also review the most common reference architectures (โpatternsโ) witnessed in customer adoption.
What Is Hadoop? | What Is Big Data & Hadoop | Introduction To Hadoop | Hadoop...Simplilearn
ย
This presentation about Hadoop will help you understand what is Big Data, what is Hadoop, how Hadoop came into existence, what are the various components of Hadoop and an explanation on Hadoop use case. In the current time, there is a lot of data being generated every day and this massive amount of data cannot be stored, processed and analyzed using the traditional ways. That is why Hadoop can into existence as a solution for Big Data. Hadoop is a framework that manages Big Data storage in a distributed way and processes it parallelly. Now, let us get started and understand the importance of Hadoop and why we actually need it.
Below topics are explained in this Hadoop presentation:
1. The rise of Big Data
2. What is Big Data?
3. Big Data and its challenges
4. Hadoop as a solution
5. What is Hadoop?
6. Components of Hadoop
7. Use case of Hadoop
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Relational databases are perhaps the most commonly used data management systems. In relational databases, data is modeled as a collection of disparate tables. In order to unify the data within these tables, a join operation is used. This operation is expensive as the amount of data grows. For information retrieval operations that do not make use of extensive joins, relational databases are an excellent tool. However, when an excessive amount of joins are required, the relational database model breaks down. In contrast, graph databases maintain one single data structure---a graph. A graph contains a set of vertices (i.e. nodes, dots) and a set of edges (i.e. links, lines). These elements make direct reference to one another, and as such, there is no notion of a join operation. The direct references between graph elements make the joining of data explicit within the structure of the graph. The benefit of this model is that traversing (i.e. moving between the elements of a graph in an intelligent, direct manner) is very efficient and yields a style of problem-solving called the graph traversal pattern. This session will discuss graph databases, the graph traversal programming pattern, and their use in solving real-world problems.
[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...DataScienceConferenc1
ย
Dragan Beriฤ will take a deep dive into Lakehouse architecture, a game-changing concept bridging the best elements of data lake and data warehouse. The presentation will focus on the Delta Lake format as the foundation of the Lakehouse philosophy, and Databricks as the primary platform for its implementation.
Hadoop Summit 2012 | Optimizing MapReduce Job PerformanceCloudera, Inc.
ย
Optimizing MapReduce job performance is often seen as something of a black art. In order to maximize performance, developers need to understand the inner workings of the MapReduce execution framework and how they are affected by various configuration parameters and MR design patterns. The talk will illustrate the underlying mechanics of job and task execution, including the map side sort/spill, the shuffle, and the reduce side merge, and then explain how different job configuration parameters and job design strategies affect the performance of these operations. Though the talk will cover internals, it will also provide practical tips, guidelines, and rules of thumb for better job performance. The talk is primarily targeted towards developers directly using the MapReduce API, though will also include some tips for users of higher level frameworks.
Learn how Amazon Redshift, our fully managed, petabyte-scale data warehouse, can help you quickly and cost-effectively analyze all your data using your existing business intelligence tools. Get an introduction to how Amazon Redshift uses massively parallel processing and scale-out architecture to ensure compute resources grow with your dataset size, and columnar, direct-attached storage to dramatically reduce I/O time. Learn how top online retailer RetailMeNot moved their largest Vertica cluster on Amazon EC2 to Amazon Redshift. See how they gain insights from clickstream, location, merchant, marketing, and operational data across desktop and mobile properties.
What Should I Do? Choosing SQL, NoSQL or Both for Scalable Web ApplicationsTodd Hoff
ย
This is the slidedeck I used for a webinar (http://voltdb.com/choosing-sql-nosql-or-both-scalable-web-apps-webinar) I gave on helping people choose SQL or NoSQL for building scalabile web applications. Hint, the answer is: both.
GT.M: A Tried and Tested Open-Source NoSQL DatabaseRob Tweed
ย
GT.M is a tried and tested schema-less "NoSQL" database with a strong pedigree in the highly demanding banking sector. Its free open-source licensing on x86 GNU Linux makes it an excellent alternative to the list of new, largely untested, NoSQL databases.
NoSQL databases get a lot of press coverage, but there seems to be a lot of confusion surrounding them, as in which situations they work better than a Relational Database, and how to choose one over another. This talk will give an overview of the NoSQL landscape and a classification for the different architectural categories, clarifying the base concepts and the terminology, and will provide a comparison of the features, the strengths and the drawbacks of the most popular projects (CouchDB, MongoDB, Riak, Redis, Membase, Neo4j, Cassandra, HBase, Hypertable).
026 Neo4j Data Loading (ETL_ELT) Best Practices - NODES2022 AMERICAS Advanced...Neo4j
ย
What patterns are most appropriate for building ETLs using Neo4j? In this session, we share how we built the Google Cloud DataFlow flex template using the Neo4j Java API. You can then apply the same approach to building read and write operators in any framework, including AWS Lambda and Google Cloud Functions.
The Future of Data Science and Machine Learning at Scale: A Look at MLflow, D...Databricks
ย
Many had dubbed 2020 as the decade of data. This is indeed an era of data zeitgeist.
From code-centric software development 1.0, we are entering software development 2.0, a data-centric and data-driven approach, where data plays a central theme in our everyday lives.
As the volume and variety of data garnered from myriad data sources continue to grow at an astronomical scale and as cloud computing offers cheap computing and data storage resources at scale, the data platforms have to match in their abilities to process, analyze, and visualize at scale and speed and with ease โ this involves data paradigm shifts in processing and storing and in providing programming frameworks to developers to access and work with these data platforms.
In this talk, we will survey some emerging technologies that address the challenges of data at scale, how these tools help data scientists and machine learning developers with their data tasks, why they scale, and how they facilitate the future data scientists to start quickly.
In particular, we will examine in detail two open-source tools MLflow (for machine learning life cycle development) and Delta Lake (for reliable storage for structured and unstructured data).
Other emerging tools such as Koalas help data scientists to do exploratory data analysis at scale in a language and framework they are familiar with as well as emerging data + AI trends in 2021.
You will understand the challenges of machine learning model development at scale, why you need reliable and scalable storage, and what other open source tools are at your disposal to do data science and machine learning at scale.
Cosco: An Efficient Facebook-Scale Shuffle ServiceDatabricks
ย
Cosco is an efficient shuffle-as-a-service that powers Spark (and Hive) jobs at Facebook warehouse scale. It is implemented as a scalable, reliable and maintainable distributed system. Cosco is based on the idea of partial in-memory aggregation across a shared pool of distributed memory. This provides vastly improved efficiency in disk usage compared to Spark's built-in shuffle. Long term, we believe the Cosco architecture will be key to efficiently supporting jobs at ever larger scale. In this talk we'll take a deep dive into the Cosco architecture and describe how it's deployed at Facebook. We will then describe how it's integrated to run shuffle for Spark, and contrast it with Spark's built-in sort-based shuffle mechanism and SOS (presented at Spark+AI Summit 2018).
Using all of the high availability options in MariaDBMariaDB plc
ย
MariaDB provides a number of high availability options, including replication with automatic failover and multi-master clustering. In this session Wagner Bianchi, Principal Remote DBA, provides a comprehensive overview of the high availability features in MariaDB, highlights their impact on consistency and performance, discusses advanced failover strategies and introduces new features such as casual reads and transparent connection failover.
Differentiate Big Data vs Data Warehouse use cases for a cloud solutionJames Serra
ย
It can be quite challenging keeping up with the frequent updates to the Microsoft products and understanding all their use cases and how all the products fit together. ย In this session we will differentiate the use cases for each of the Microsoft services, explaining and demonstrating what is good and what isn't, in order for you to position, design and deliver the proper adoption use cases for each with your customers. ย We will cover a wide range of products such as Databricks, SQL Data Warehouse, HDInsight, Azure Data Lake Analytics, Azure Data Lake Store, Blob storage, and AAS ย as well as high-level concepts such as when to use a data lake.ย We will also review the most common reference architectures (โpatternsโ) witnessed in customer adoption.
What Is Hadoop? | What Is Big Data & Hadoop | Introduction To Hadoop | Hadoop...Simplilearn
ย
This presentation about Hadoop will help you understand what is Big Data, what is Hadoop, how Hadoop came into existence, what are the various components of Hadoop and an explanation on Hadoop use case. In the current time, there is a lot of data being generated every day and this massive amount of data cannot be stored, processed and analyzed using the traditional ways. That is why Hadoop can into existence as a solution for Big Data. Hadoop is a framework that manages Big Data storage in a distributed way and processes it parallelly. Now, let us get started and understand the importance of Hadoop and why we actually need it.
Below topics are explained in this Hadoop presentation:
1. The rise of Big Data
2. What is Big Data?
3. Big Data and its challenges
4. Hadoop as a solution
5. What is Hadoop?
6. Components of Hadoop
7. Use case of Hadoop
What is this Big Data Hadoop training course about?
The Big Data Hadoop and Spark developer course have been designed to impart in-depth knowledge of Big Data processing using Hadoop and Spark. The course is packed with real-life projects and case studies to be executed in the CloudLab.
What are the course objectives?
This course will enable you to:
1. Understand the different components of the Hadoop ecosystem such as Hadoop 2.7, Yarn, MapReduce, Pig, Hive, Impala, HBase, Sqoop, Flume, and Apache Spark
2. Understand Hadoop Distributed File System (HDFS) and YARN as well as their architecture, and learn how to work with them for storage and resource management
3. Understand MapReduce and its characteristics, and assimilate some advanced MapReduce concepts
4. Get an overview of Sqoop and Flume and describe how to ingest data using them
5. Create database and tables in Hive and Impala, understand HBase, and use Hive and Impala for partitioning
6. Understand different types of file formats, Avro Schema, using Arvo with Hive, and Sqoop and Schema evolution
7. Understand Flume, Flume architecture, sources, flume sinks, channels, and flume configurations
8. Understand HBase, its architecture, data storage, and working with HBase. You will also understand the difference between HBase and RDBMS
9. Gain a working knowledge of Pig and its components
10. Do functional programming in Spark
11. Understand resilient distribution datasets (RDD) in detail
12. Implement and build Spark applications
13. Gain an in-depth understanding of parallel processing in Spark and Spark RDD optimization techniques
14. Understand the common use-cases of Spark and the various interactive algorithms
15. Learn Spark SQL, creating, transforming, and querying Data frames
Learn more at https://www.simplilearn.com/big-data-and-analytics/big-data-and-hadoop-training
Relational databases are perhaps the most commonly used data management systems. In relational databases, data is modeled as a collection of disparate tables. In order to unify the data within these tables, a join operation is used. This operation is expensive as the amount of data grows. For information retrieval operations that do not make use of extensive joins, relational databases are an excellent tool. However, when an excessive amount of joins are required, the relational database model breaks down. In contrast, graph databases maintain one single data structure---a graph. A graph contains a set of vertices (i.e. nodes, dots) and a set of edges (i.e. links, lines). These elements make direct reference to one another, and as such, there is no notion of a join operation. The direct references between graph elements make the joining of data explicit within the structure of the graph. The benefit of this model is that traversing (i.e. moving between the elements of a graph in an intelligent, direct manner) is very efficient and yields a style of problem-solving called the graph traversal pattern. This session will discuss graph databases, the graph traversal programming pattern, and their use in solving real-world problems.
[DSC Europe 22] Lakehouse architecture with Delta Lake and Databricks - Draga...DataScienceConferenc1
ย
Dragan Beriฤ will take a deep dive into Lakehouse architecture, a game-changing concept bridging the best elements of data lake and data warehouse. The presentation will focus on the Delta Lake format as the foundation of the Lakehouse philosophy, and Databricks as the primary platform for its implementation.
Hadoop Summit 2012 | Optimizing MapReduce Job PerformanceCloudera, Inc.
ย
Optimizing MapReduce job performance is often seen as something of a black art. In order to maximize performance, developers need to understand the inner workings of the MapReduce execution framework and how they are affected by various configuration parameters and MR design patterns. The talk will illustrate the underlying mechanics of job and task execution, including the map side sort/spill, the shuffle, and the reduce side merge, and then explain how different job configuration parameters and job design strategies affect the performance of these operations. Though the talk will cover internals, it will also provide practical tips, guidelines, and rules of thumb for better job performance. The talk is primarily targeted towards developers directly using the MapReduce API, though will also include some tips for users of higher level frameworks.
Learn how Amazon Redshift, our fully managed, petabyte-scale data warehouse, can help you quickly and cost-effectively analyze all your data using your existing business intelligence tools. Get an introduction to how Amazon Redshift uses massively parallel processing and scale-out architecture to ensure compute resources grow with your dataset size, and columnar, direct-attached storage to dramatically reduce I/O time. Learn how top online retailer RetailMeNot moved their largest Vertica cluster on Amazon EC2 to Amazon Redshift. See how they gain insights from clickstream, location, merchant, marketing, and operational data across desktop and mobile properties.
What Should I Do? Choosing SQL, NoSQL or Both for Scalable Web ApplicationsTodd Hoff
ย
This is the slidedeck I used for a webinar (http://voltdb.com/choosing-sql-nosql-or-both-scalable-web-apps-webinar) I gave on helping people choose SQL or NoSQL for building scalabile web applications. Hint, the answer is: both.
GT.M: A Tried and Tested Open-Source NoSQL DatabaseRob Tweed
ย
GT.M is a tried and tested schema-less "NoSQL" database with a strong pedigree in the highly demanding banking sector. Its free open-source licensing on x86 GNU Linux makes it an excellent alternative to the list of new, largely untested, NoSQL databases.
Embracing Open Source: Practice and Experience from AlibabaWensong Zhang
ย
Alibaba Group is one of the most active companies involved in open source in China. Why Alibaba actively embrace open source? what open source projects we have been participating? and what we gain in open source development? This talk will give a brief introduction about Alibaba Group, will take Taobao.com as an example for building software infrastructure based on open source software and home grown software, where picture storage system, CDN system and database system will be presented to see how the systems were evolved from commercial products at the beginning, and will conclude some experience during this process. Then, it will list major open source projects that Alibaba have started and been involved, and will share open source procedure in the company. Finally, it will discuss the benefits of open source development from both developer perspective and company perspective, and conclude the reasons of embracing open source.
DevOps, PaaS and the Modern Enterprise CloudExpo Europe presentation by Diane...OpenShift Origin
ย
The rise in application complexity is answered by the emergence of DevOps and simplified by adding a PaaS bringing agility, speed, and compliance to the modern Enterprise.
From Zero to Cloud: Revolutionize your Application Life Cycle with OpenShift ...OpenShift Origin
ย
From Zero to Cloud: Revolutionize your Application Life Cycle with OpenShift PaaS
Talk given by Diane Mueller, OpenShift Origin Community Manager at FISL 15 on May 9th, 2014
Pros and Cons of MongoDB in Web DevelopmentNirvana Canada
ย
Databases are available in plenty, and choosing the right one for your organization is a challenging task. In this blog, we will specifically focus on MongoDB and its pros and cons for web development.
how_can_businesses_address_storage_issues_using_mongodb.pdfsarah david
ย
MongoDB enables seamless data storage and performance. Explore our blog to learn how MongoDB handles storage issues for startups and large-scale enterprises. Discover how to optimize MongoDB performance using open-source database storage.
Big data, agile development, and cloud computing
are driving new requirements for database
management systems. These requirements are in turn
driving the next phase of growth in the database
industry, mirroring the evolution of the OLAP
industry. This document describes this evolution, the
new application workload, and how MongoDB is
uniquely suited to address these challenges.
how_can_businesses_address_storage_issues_using_mongodb.pptxsarah david
ย
MongoDB enables seamless data storage and performance. Explore our blog to learn how MongoDB handles storage issues for startups and large-scale enterprises. Discover how to optimize MongoDB performance using open-source database storage.
When it comes time to select database software for your project, there are a bewildering number of choices. How do you know if your project is a good fit for a relational database, or whether one of the many NoSQL options is a better choice?
In this webinar you will learn when to use MongoDB and how to evaluate if MongoDB is a fit for your project. You will see how MongoDB's flexible document model is solving business problems in ways that were not previously possible, and how MongoDB's built-in features allow running at scale.
Topics covered include:
Performance and Scalability
MongoDB's Data Model
Popular MongoDB Use Cases
Customer Stories
Putting the SPARK into Virtual Training.pptxCynthia Clay
ย
This 60-minute webinar, sponsored by Adobe, was delivered for the Training Mag Network. It explored the five elements of SPARK: Storytelling, Purpose, Action, Relationships, and Kudos. Knowing how to tell a well-structured story is key to building long-term memory. Stating a clear purpose that doesn't take away from the discovery learning process is critical. Ensuring that people move from theory to practical application is imperative. Creating strong social learning is the key to commitment and engagement. Validating and affirming participants' comments is the way to create a positive learning environment.
"๐ฉ๐ฌ๐ฎ๐ผ๐ต ๐พ๐ฐ๐ป๐ฏ ๐ป๐ฑ ๐ฐ๐บ ๐ฏ๐จ๐ณ๐ญ ๐ซ๐ถ๐ต๐ฌ"
๐๐ ๐๐จ๐ฆ๐ฌ (๐๐ ๐๐จ๐ฆ๐ฆ๐ฎ๐ง๐ข๐๐๐ญ๐ข๐จ๐ง๐ฌ) is a professional event agency that includes experts in the event-organizing market in Vietnam, Korea, and ASEAN countries. We provide unlimited types of events from Music concerts, Fan meetings, and Culture festivals to Corporate events, Internal company events, Golf tournaments, MICE events, and Exhibitions.
๐๐ ๐๐จ๐ฆ๐ฌ provides unlimited package services including such as Event organizing, Event planning, Event production, Manpower, PR marketing, Design 2D/3D, VIP protocols, Interpreter agency, etc.
Sports events - Golf competitions/billiards competitions/company sports events: dynamic and challenging
โญ ๐ ๐๐๐ญ๐ฎ๐ซ๐๐ ๐ฉ๐ซ๐จ๐ฃ๐๐๐ญ๐ฌ:
โข 2024 BAEKHYUN [Lonsdaleite] IN HO CHI MINH
โข SUPER JUNIOR-L.S.S. THE SHOW : Th3ee Guys in HO CHI MINH
โขFreenBecky 1st Fan Meeting in Vietnam
โขCHILDREN ART EXHIBITION 2024: BEYOND BARRIERS
โข WOW K-Music Festival 2023
โข Winner [CROSS] Tour in HCM
โข Super Show 9 in HCM with Super Junior
โข HCMC - Gyeongsangbuk-do Culture and Tourism Festival
โข Korean Vietnam Partnership - Fair with LG
โข Korean President visits Samsung Electronics R&D Center
โข Vietnam Food Expo with Lotte Wellfood
"๐๐ฏ๐๐ซ๐ฒ ๐๐ฏ๐๐ง๐ญ ๐ข๐ฌ ๐ ๐ฌ๐ญ๐จ๐ซ๐ฒ, ๐ ๐ฌ๐ฉ๐๐๐ข๐๐ฅ ๐ฃ๐จ๐ฎ๐ซ๐ง๐๐ฒ. ๐๐ ๐๐ฅ๐ฐ๐๐ฒ๐ฌ ๐๐๐ฅ๐ข๐๐ฏ๐ ๐ญ๐ก๐๐ญ ๐ฌ๐ก๐จ๐ซ๐ญ๐ฅ๐ฒ ๐ฒ๐จ๐ฎ ๐ฐ๐ข๐ฅ๐ฅ ๐๐ ๐ ๐ฉ๐๐ซ๐ญ ๐จ๐ ๐จ๐ฎ๐ซ ๐ฌ๐ญ๐จ๐ซ๐ข๐๐ฌ."
Personal Brand Statement:
As an Army veteran dedicated to lifelong learning, I bring a disciplined, strategic mindset to my pursuits. I am constantly expanding my knowledge to innovate and lead effectively. My journey is driven by a commitment to excellence, and to make a meaningful impact in the world.
Implicitly or explicitly all competing businesses employ a strategy to select a mix
of marketing resources. Formulating such competitive strategies fundamentally
involves recognizing relationships between elements of the marketing mix (e.g.,
price and product quality), as well as assessing competitive and market conditions
(i.e., industry structure in the language of economics).
3.0 Project 2_ Developing My Brand Identity Kit.pptxtanyjahb
ย
A personal brand exploration presentation summarizes an individual's unique qualities and goals, covering strengths, values, passions, and target audience. It helps individuals understand what makes them stand out, their desired image, and how they aim to achieve it.
Kseniya Leshchenko: Shared development support service model as the way to ma...Lviv Startup Club
ย
Kseniya Leshchenko: Shared development support service model as the way to make small projects with small budgets profitable for the company (UA)
Kyiv PMDay 2024 Summer
Website โ www.pmday.org
Youtube โ https://www.youtube.com/startuplviv
FB โ https://www.facebook.com/pmdayconference
Buy Verified PayPal Account | Buy Google 5 Star Reviewsusawebmarket
ย
Buy Verified PayPal Account
Looking to buy verified PayPal accounts? Discover 7 expert tips for safely purchasing a verified PayPal account in 2024. Ensure security and reliability for your transactions.
PayPal Services Features-
๐ข Email Access
๐ข Bank Added
๐ข Card Verified
๐ข Full SSN Provided
๐ข Phone Number Access
๐ข Driving License Copy
๐ข Fasted Delivery
Client Satisfaction is Our First priority. Our services is very appropriate to buy. We assume that the first-rate way to purchase our offerings is to order on the website. If you have any worry in our cooperation usually You can order us on Skype or Telegram.
24/7 Hours Reply/Please Contact
usawebmarketEmail: support@usawebmarket.com
Skype: usawebmarket
Telegram: @usawebmarket
WhatsApp: +1โช(218) 203-5951โฌ
USA WEB MARKET is the Best Verified PayPal, Payoneer, Cash App, Skrill, Neteller, Stripe Account and SEO, SMM Service provider.100%Satisfection granted.100% replacement Granted.
Tata Group Dials Taiwan for Its Chipmaking Ambition in Gujaratโs DholeraAvirahi City Dholera
ย
The Tata Group, a titan of Indian industry, is making waves with its advanced talks with Taiwanese chipmakers Powerchip Semiconductor Manufacturing Corporation (PSMC) and UMC Group. The goal? Establishing a cutting-edge semiconductor fabrication unit (fab) in Dholera, Gujarat. This isnโt just any project; itโs a potential game changer for Indiaโs chipmaking aspirations and a boon for investors seeking promisingย residential projects in dholera sir.
Visit : https://www.avirahi.com/blog/tata-group-dials-taiwan-for-its-chipmaking-ambition-in-gujarats-dholera/
Enterprise Excellence is Inclusive Excellence.pdfKaiNexus
ย
Enterprise excellence and inclusive excellence are closely linked, and real-world challenges have shown that both are essential to the success of any organization. To achieve enterprise excellence, organizations must focus on improving their operations and processes while creating an inclusive environment that engages everyone. In this interactive session, the facilitator will highlight commonly established business practices and how they limit our ability to engage everyone every day. More importantly, though, participants will likely gain increased awareness of what we can do differently to maximize enterprise excellence through deliberate inclusion.
What is Enterprise Excellence?
Enterprise Excellence is a holistic approach that's aimed at achieving world-class performance across all aspects of the organization.
What might I learn?
A way to engage all in creating Inclusive Excellence. Lessons from the US military and their parallels to the story of Harry Potter. How belt systems and CI teams can destroy inclusive practices. How leadership language invites people to the party. There are three things leaders can do to engage everyone every day: maximizing psychological safety to create environments where folks learn, contribute, and challenge the status quo.
Who might benefit? Anyone and everyone leading folks from the shop floor to top floor.
Dr. William Harvey is a seasoned Operations Leader with extensive experience in chemical processing, manufacturing, and operations management. At Michelman, he currently oversees multiple sites, leading teams in strategic planning and coaching/practicing continuous improvement. William is set to start his eighth year of teaching at the University of Cincinnati where he teaches marketing, finance, and management. William holds various certifications in change management, quality, leadership, operational excellence, team building, and DiSC, among others.
Unveiling the Secrets How Does Generative AI Work.pdfSam H
ย
At its core, generative artificial intelligence relies on the concept of generative models, which serve as engines that churn out entirely new data resembling their training data. It is like a sculptor who has studied so many forms found in nature and then uses this knowledge to create sculptures from his imagination that have never been seen before anywhere else. If taken to cyberspace, gans work almost the same way.
Memorandum Of Association Constitution of Company.pptseri bangash
ย
www.seribangash.com
A Memorandum of Association (MOA) is a legal document that outlines the fundamental principles and objectives upon which a company operates. It serves as the company's charter or constitution and defines the scope of its activities. Here's a detailed note on the MOA:
Contents of Memorandum of Association:
Name Clause: This clause states the name of the company, which should end with words like "Limited" or "Ltd." for a public limited company and "Private Limited" or "Pvt. Ltd." for a private limited company.
https://seribangash.com/article-of-association-is-legal-doc-of-company/
Registered Office Clause: It specifies the location where the company's registered office is situated. This office is where all official communications and notices are sent.
Objective Clause: This clause delineates the main objectives for which the company is formed. It's important to define these objectives clearly, as the company cannot undertake activities beyond those mentioned in this clause.
www.seribangash.com
Liability Clause: It outlines the extent of liability of the company's members. In the case of companies limited by shares, the liability of members is limited to the amount unpaid on their shares. For companies limited by guarantee, members' liability is limited to the amount they undertake to contribute if the company is wound up.
https://seribangash.com/promotors-is-person-conceived-formation-company/
Capital Clause: This clause specifies the authorized capital of the company, i.e., the maximum amount of share capital the company is authorized to issue. It also mentions the division of this capital into shares and their respective nominal value.
Association Clause: It simply states that the subscribers wish to form a company and agree to become members of it, in accordance with the terms of the MOA.
Importance of Memorandum of Association:
Legal Requirement: The MOA is a legal requirement for the formation of a company. It must be filed with the Registrar of Companies during the incorporation process.
Constitutional Document: It serves as the company's constitutional document, defining its scope, powers, and limitations.
Protection of Members: It protects the interests of the company's members by clearly defining the objectives and limiting their liability.
External Communication: It provides clarity to external parties, such as investors, creditors, and regulatory authorities, regarding the company's objectives and powers.
https://seribangash.com/difference-public-and-private-company-law/
Binding Authority: The company and its members are bound by the provisions of the MOA. Any action taken beyond its scope may be considered ultra vires (beyond the powers) of the company and therefore void.
Amendment of MOA:
While the MOA lays down the company's fundamental principles, it is not entirely immutable. It can be amended, but only under specific circumstances and in compliance with legal procedures. Amendments typically require shareholder
38. What is MongoDB?
Is a scalable, high-performance, open source,
document-oriented persistent storage engine,
where bridges the gap between key-value stores
and traditional RDBMS systems.