Brief Introduction to ETL, showing:
- its advantages
- differences from normal applications
The Live Talend Demo was given at Software Niagara's DevTricks on Oct. 17, 2016.
If you want to learn more about ETL, please contact me.
SAS Online Training Institute in Hyderabad - C-Pointcpointss
C-Point Software Solutions is a Leading Training Institute in Hyderabad. We Provide Training on SAP, SAS, Oracle E Business Suite, Informatica, OBIEE, SQL DBA, Hadoop, Cloud Computing, .Net, Testing Tools, Java, Web Designing, PHP.
Light up Your Dark Data by Lance Ransom at QuantCon 2016Quantopian
Quants are faced with a complex data environment. Data is everywhere and it's increasingly challenging to analyze, explore and evaluate, all in one language and in one environment. Quants need a unified environment where they are able to write expressions and conduct pushdown processes, all without having to move the data and having the ability to deploy anywhere, anytime. Organizations need to better marshal the data and have visibility to conduct a clean transformation. This session will discuss how businesses gain a better understanding of their data, leading to better results. In the FinServ industry, fluidity in understanding the data will help create better risk models and trading strategies. Ransom will discuss how organizations address these challenges and future proof their work.
SAS Online Training Institute in Hyderabad - C-Pointcpointss
C-Point Software Solutions is a Leading Training Institute in Hyderabad. We Provide Training on SAP, SAS, Oracle E Business Suite, Informatica, OBIEE, SQL DBA, Hadoop, Cloud Computing, .Net, Testing Tools, Java, Web Designing, PHP.
Light up Your Dark Data by Lance Ransom at QuantCon 2016Quantopian
Quants are faced with a complex data environment. Data is everywhere and it's increasingly challenging to analyze, explore and evaluate, all in one language and in one environment. Quants need a unified environment where they are able to write expressions and conduct pushdown processes, all without having to move the data and having the ability to deploy anywhere, anytime. Organizations need to better marshal the data and have visibility to conduct a clean transformation. This session will discuss how businesses gain a better understanding of their data, leading to better results. In the FinServ industry, fluidity in understanding the data will help create better risk models and trading strategies. Ransom will discuss how organizations address these challenges and future proof their work.
Join us and learn how to use Addins for some simple queries and data loads.
A brief overview of Lawson MS Addins. The presentation covers:
Introduction to Lawson Add-Ins for Microsoft Office
Navigation and logging in to the Addins
Query Wizard
Inqueries
Uploads
Advanced Tools
Troubleshooting
Express Yourself: Building Expressions with Microsoft Flow - SPSCLT 2018Fausto Capellan Jr
This session was presented at the SharePoint Saturday Charlotte on August 11th, 2018. This session covers how to get started building expressions in Microsoft Flow.
TaLend Online Training is offering at Glory IT Technologies. We have best professionals for Talend Training and our trainers have more experienced. We will traine students as per the Current IT requirments.
LINQ stands for Language Integrated Query.
A query is an expression that retrieves data from a data source or database.
Retrieve data from different data source like an object collection, sql server database, xml & web service etc.
LINQ Syntax like- var students = dbContext.Students.ToList();
Presented by Jennifer Hecker and Elizabeth Grumbach and hosted by the Texas Consortium on Digital Humanities, these are the slides for the TXDHC training webcast on OpenRefine, February 12th, 2015.
Data lineage has gained popularity in the Machine Learning community as a way to make models and datasets easier to interpret and to help developers debug their ML pipelines by enabling them to go from a model to the dataset/user who trained it. Data provenance and lineage is the process of building up the history of how a data artifact came to be. This history of derivations and interactions can provide a better context for data discovery, debugging, as well as auditing. In this area, others, such as Google and Databricks, have made small steps.
The Hopsworks approach presented provenance information is collected implicitly through the unobtrusive instrumentation of jupyter notebooks and python code - What we call 'implicit provenance'.
How’d you like to learn to build a simple ProcessFlow in just 30 minutes? Join us for this webinar.
A brief overview of ProcessFlow. The presentation covers:
What is ProcessFlow?
Introduction to components and terminology
Building an actual flow
Implementation methodology
Troubleshooting
Although you may not have heard of JavaScript Object Notation Linked Data (JSON-LD), it is already impacting your business. Search engine giants such as Google have mandated JSON-LD as a preferred means of adding structured data to web pages to make them considerably easier to parse for more accurate search engine results. The Google use case is indicative of the larger capacity for JSON-LD to increase web traffic for sites and better guide users to the results they want.
Expectations are high for (JSON-LD), and with good reason. JSON-LD effectively delivers the many benefits of JSON, a lightweight data interchange format, into the linked data world. Linked data is the technological approach supporting the World Wide Web and one of the most effective means of sharing data ever devised.
In addition, the growing number of enterprise knowledge graphs fully exploit the potential of JSON-LD as it enables organizations to readily access data stored in document formats and a variety of semi-structured and unstructured data as well. By using this technology to link internal and external data, knowledge graphs exemplify the linked data approach underpinning the growing adoption of JSON-LD—and the demonstrable, recurring business value that linked data consistently provides.
Join us learn more about optimizing the unique Document and Graph Database capabilities provided by AllegroGraph to develop or enhance your Enterprise Knowledge Graph using JSON-LD.
Totango is an Analytics platform for Customer Success.
Our data pipeline converts usage information into actionable analytics. The pipeline is managed using Luigi workflow engine, and data transformations are done in Spark.
(BDT303) Construct Your ETL Pipeline with AWS Data Pipeline, Amazon EMR, and ...Amazon Web Services
An advantage to leveraging Amazon Web Services for your data processing and warehousing use cases is the number of services available to construct complex, automated architectures easily. Using AWS Data Pipeline, Amazon EMR, and Amazon Redshift, we show you how to build a fault-tolerant, highly available, and highly scalable ETL pipeline and data warehouse. Coursera will show how they built their pipeline, and share best practices from their architecture.
Join us and learn how to use Addins for some simple queries and data loads.
A brief overview of Lawson MS Addins. The presentation covers:
Introduction to Lawson Add-Ins for Microsoft Office
Navigation and logging in to the Addins
Query Wizard
Inqueries
Uploads
Advanced Tools
Troubleshooting
Express Yourself: Building Expressions with Microsoft Flow - SPSCLT 2018Fausto Capellan Jr
This session was presented at the SharePoint Saturday Charlotte on August 11th, 2018. This session covers how to get started building expressions in Microsoft Flow.
TaLend Online Training is offering at Glory IT Technologies. We have best professionals for Talend Training and our trainers have more experienced. We will traine students as per the Current IT requirments.
LINQ stands for Language Integrated Query.
A query is an expression that retrieves data from a data source or database.
Retrieve data from different data source like an object collection, sql server database, xml & web service etc.
LINQ Syntax like- var students = dbContext.Students.ToList();
Presented by Jennifer Hecker and Elizabeth Grumbach and hosted by the Texas Consortium on Digital Humanities, these are the slides for the TXDHC training webcast on OpenRefine, February 12th, 2015.
Data lineage has gained popularity in the Machine Learning community as a way to make models and datasets easier to interpret and to help developers debug their ML pipelines by enabling them to go from a model to the dataset/user who trained it. Data provenance and lineage is the process of building up the history of how a data artifact came to be. This history of derivations and interactions can provide a better context for data discovery, debugging, as well as auditing. In this area, others, such as Google and Databricks, have made small steps.
The Hopsworks approach presented provenance information is collected implicitly through the unobtrusive instrumentation of jupyter notebooks and python code - What we call 'implicit provenance'.
How’d you like to learn to build a simple ProcessFlow in just 30 minutes? Join us for this webinar.
A brief overview of ProcessFlow. The presentation covers:
What is ProcessFlow?
Introduction to components and terminology
Building an actual flow
Implementation methodology
Troubleshooting
Although you may not have heard of JavaScript Object Notation Linked Data (JSON-LD), it is already impacting your business. Search engine giants such as Google have mandated JSON-LD as a preferred means of adding structured data to web pages to make them considerably easier to parse for more accurate search engine results. The Google use case is indicative of the larger capacity for JSON-LD to increase web traffic for sites and better guide users to the results they want.
Expectations are high for (JSON-LD), and with good reason. JSON-LD effectively delivers the many benefits of JSON, a lightweight data interchange format, into the linked data world. Linked data is the technological approach supporting the World Wide Web and one of the most effective means of sharing data ever devised.
In addition, the growing number of enterprise knowledge graphs fully exploit the potential of JSON-LD as it enables organizations to readily access data stored in document formats and a variety of semi-structured and unstructured data as well. By using this technology to link internal and external data, knowledge graphs exemplify the linked data approach underpinning the growing adoption of JSON-LD—and the demonstrable, recurring business value that linked data consistently provides.
Join us learn more about optimizing the unique Document and Graph Database capabilities provided by AllegroGraph to develop or enhance your Enterprise Knowledge Graph using JSON-LD.
Totango is an Analytics platform for Customer Success.
Our data pipeline converts usage information into actionable analytics. The pipeline is managed using Luigi workflow engine, and data transformations are done in Spark.
(BDT303) Construct Your ETL Pipeline with AWS Data Pipeline, Amazon EMR, and ...Amazon Web Services
An advantage to leveraging Amazon Web Services for your data processing and warehousing use cases is the number of services available to construct complex, automated architectures easily. Using AWS Data Pipeline, Amazon EMR, and Amazon Redshift, we show you how to build a fault-tolerant, highly available, and highly scalable ETL pipeline and data warehouse. Coursera will show how they built their pipeline, and share best practices from their architecture.
The process of extracting data from source systems and bringing it into the data warehouse is commonly called ETL, which stands for extraction, transformation, and loading.
WEBINAR: Proven Patterns for Loading Test Data for Managed Package TestingCodeScience
Scratch orgs are extremely valuable tools for Salesforce developers, but due to their individual, disposable nature, a source of truth for QA data is often not accounted for. Without a single repository for QA data, many developers may be testing against incomplete data sets, skewing their results. In our latest tech webinar, we discuss implications planning for QA data can have on Salesforce development.
In this webinar, you will learn:
- Why it’s essential to have a plan in place early on how to deploy data to scratch orgs and QA orgs.
- Shortcuts which can inadvertently hide bugs that don't manifest until tested with real data, and lengthen the time it takes to complete a task.
- Strategies for maintaining data models as projects progress and as data is added or removed to stay realistic and current.
CodeScience Lead Salesforce Developer, Bobby Tamburrino will dive into these topics and provide key insights that can help ISVs succeed on the AppExchange.
Solving Data Discovery Challenges at Lyft with Amundsen, an Open-source Metad...Databricks
Amundsen is the data discovery metadata platform that originated from Lyft which is recently donated to Linux Foundation AI. Since its open-sourced, Amundsen has been used and extended by many different companies within our community.
Slides from Salesforce bangalore developer group event organised at UrbanLadder on "Salesforce Connect".
Salesforce Connect is a framework that enables you to view, search, and modify data that’s stored outside your Salesforce org.
Pentaho Data Integration in Data Warehouse.
Open-source Pentaho provides business intelligence (BI) and data warehousing solutions at a fraction of the cost of proprietary solutions.
Pentaho Data Integration (PDI) provides the Extract, Transform, and Load (ETL) capabilities that facilitates the process of capturing, cleansing, and storing data using a uniform and consistent format that is accessible and relevant to end users and IoT technologies
By Muhammad Ayaz Farid Shah.
03446940736.
MSCS.
Using Databricks as an Analysis PlatformDatabricks
Over the past year, YipitData spearheaded a full migration of its data pipelines to Apache Spark via the Databricks platform. Databricks now empowers its 40+ data analysts to independently create data ingestion systems, manage ETL workflows, and produce meaningful financial research for our clients.
Warehousing Your Hits - The Why and How of Owning Your DataScott Arbeitman
These are the slides from my recent presentation at Melbourne' Web Analytics Wednesdays. I talk about transitioning from collecting your data in primary digital analytics systems to storing them in a data warehouse or data lake.
Intro to Talend Open Studio for Data IntegrationPhilip Yurchuk
An overview of Talend Open Studio for Data Integration, along with some tips learned from building production jobs and a list of resources. Feel free to contact me for more information.
The most important thing for any organization is DATA. There can be 100 of front end applications which utilizing the same data for different purpose. Data plays an important role for any CMS application. This presentation touches different viewpoint while migrating data from external database to Sitecore CMS.
By using these details we able to successfully migrate over 5,00,000+ records in Sitecore.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
StarCompliance is a leading firm specializing in the recovery of stolen cryptocurrency. Our comprehensive services are designed to assist individuals and organizations in navigating the complex process of fraud reporting, investigation, and fund recovery. We combine cutting-edge technology with expert legal support to provide a robust solution for victims of crypto theft.
Our Services Include:
Reporting to Tracking Authorities:
We immediately notify all relevant centralized exchanges (CEX), decentralized exchanges (DEX), and wallet providers about the stolen cryptocurrency. This ensures that the stolen assets are flagged as scam transactions, making it impossible for the thief to use them.
Assistance with Filing Police Reports:
We guide you through the process of filing a valid police report. Our support team provides detailed instructions on which police department to contact and helps you complete the necessary paperwork within the critical 72-hour window.
Launching the Refund Process:
Our team of experienced lawyers can initiate lawsuits on your behalf and represent you in various jurisdictions around the world. They work diligently to recover your stolen funds and ensure that justice is served.
At StarCompliance, we understand the urgency and stress involved in dealing with cryptocurrency theft. Our dedicated team works quickly and efficiently to provide you with the support and expertise needed to recover your assets. Trust us to be your partner in navigating the complexities of the crypto world and safeguarding your investments.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
2. About the Author
Maira Bay de Souza, BSc. Comp.
Science
Working with
● software testing
● software development
since 2001
Talend ETL developer and tester since
2013
IBM, HP, SunLife, small businesses
3. What is ETL?
● Extract, Transform, Load
● Sequence of operations on the same dataset
● Sometimes joining datasets together in T
● Simple Transformations may be done in E, L
4. Extract
Read any kind of static data source:
● Extract data from a website (HTML, JSON,
RSS, etc)
● Read files from a server (FTP, SCP, etc)
● Query a RESTful API
● Read from a database
● Read from a cloud storage unit: GoogleDrive,
GoogleStorage, AWS, DropBox, etc
● Read data from common business applications:
SAP, SalesForce, SugarCRM, etc
5. Transform
Make operations on data as a whole:
● Split names into first, middle, last
● Filter out people with blank addresses
● Sort employees by % of sales target achived
● Join data from an excel file and a database
● Find duplicate names using Levenstein
● Normalize or denormalize list of addresses
● Split postal code based on Regex
● Validate XML with XSD
6. Load
Output data in any kind of format:
● Save a CSV, XML, etc
● Insert or Update a table in a database
● Send a file in an email
● Make a JSON available through a RESTful API
● Save data on a cloud storage unit:GoogleDrive,
GoogleStorage, AWS, DropBox, etc
● Save data on common business applications:
SAP, SalesForce, SugarCRM, etc
7. Example applications
● Find twitter followers who are not facebook
followers and make their names and logins
available on a JSON via RESTful API
● Join employee names from HR database with
sales records from CRM and send weekly
email to CMO with names and progress
towards sales target
8. Difference between ETL and
WebApp
WebApp
● Reads one or more user inputs
or actions:
– forms filled
– button clicked
– etc
● Produces a result:
– page updated
– page loaded
– etc
ETL
● Reads one or more data inputs:
– table from database
– pages from RSS feed
– etc
● Produces another data output or
action:
– send email
– create Jasper Report
– etc