Are you having doubts and questions about how to use Big Data in your organizations? The presentation here would clear some of your doubts.
Feel free to comment if you have more queries or write to us at: bigdata@xoriant.com
Implementation of Big Data infrastructure and technology can be seen in various industries like banking, retail, insurance, healthcare, media, etc. Big Data management functions like storage, sorting, processing and analysis for such colossal volumes cannot be handled by the existing database systems or technologies. Frameworks come into picture in such scenarios. Frameworks are nothing but toolsets that offer innovative, cost-effective solutions to the problems posed by Big Data processing and helps in providing insights, incorporating metadata and aids decision making aligned to the business needs.
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Take this opportunity to learn more about how Robotic Process Automation (RPA) play a role with your ERP. Learn more about the use of RPA for ERP-driven processes and how they can help organizations like yours make routine, time-consuming tasks less expensive and less labor-intensive.
Presented by Lewis Hopkins, Senior Technology Specialist, Smart ERP Solutions, discusses current automation trends and challenges along with providing insight on how the automation technology can have a significant impact on your organization. This webinar will included a demonstration of how bots can assist organizations with better workflows and enhanced customer service.
Learn how you can rapidly scale RPA across the organization by leveraging agile methodologies. Identify and validate automation opportunities, prioritise and deliver it continuously.
Watch The Webinar:
https://hexaware.com/resource/automation-coe-at-scale-using-agile-to-build-rpa/
Automate data warehouse etl testing and migration testing the agile wayTorana, Inc.
Data Warehouse, ETL & Migration projects are exposed to huge financial risks due to lack of QA automation. At iCEDQ, we suggest the agile rules based testing approach for all data integration projects.
Implementation of Big Data infrastructure and technology can be seen in various industries like banking, retail, insurance, healthcare, media, etc. Big Data management functions like storage, sorting, processing and analysis for such colossal volumes cannot be handled by the existing database systems or technologies. Frameworks come into picture in such scenarios. Frameworks are nothing but toolsets that offer innovative, cost-effective solutions to the problems posed by Big Data processing and helps in providing insights, incorporating metadata and aids decision making aligned to the business needs.
Business Intelligence (BI) and Data Management Basics amorshed
A one-day training course on the Concepts of Data Management and Business Intelligence (BI) in the DX age
A Basic Review of BI and DM
How to Implement BI
A review of BI Tools and 2022 Gartner Quadrant Magic
Basics of Data warehouse (DWH)
An introductions to Power BI
Components of Power BI
Steps for BI Implementation
Data Culture
Intro to ETL and ELT
OLAP files and Architecture
Digital transformation or DX review
A glance at DMBOK2.0 framework
BI Challenges
Data Governance
Data Integration
Data Security and Privacy in DMBOK2.0
Data-Driven Organization
Data and BI Maturity Model
Traditional BI
Self-service BI
who is DMP
who is BI developer
what is Metadata
what is Master data
Data Quality
Data Literacy
Benefits of BI
BI features
How does BI Works?
Modern BI
Data Analytics
BI Architecture
Data Types
Data Lake
Data Mart
Data Silo
Data Visualization
Power BI Architecture and components
Take this opportunity to learn more about how Robotic Process Automation (RPA) play a role with your ERP. Learn more about the use of RPA for ERP-driven processes and how they can help organizations like yours make routine, time-consuming tasks less expensive and less labor-intensive.
Presented by Lewis Hopkins, Senior Technology Specialist, Smart ERP Solutions, discusses current automation trends and challenges along with providing insight on how the automation technology can have a significant impact on your organization. This webinar will included a demonstration of how bots can assist organizations with better workflows and enhanced customer service.
Learn how you can rapidly scale RPA across the organization by leveraging agile methodologies. Identify and validate automation opportunities, prioritise and deliver it continuously.
Watch The Webinar:
https://hexaware.com/resource/automation-coe-at-scale-using-agile-to-build-rpa/
Automate data warehouse etl testing and migration testing the agile wayTorana, Inc.
Data Warehouse, ETL & Migration projects are exposed to huge financial risks due to lack of QA automation. At iCEDQ, we suggest the agile rules based testing approach for all data integration projects.
Gateways to Power BI, Connect PowerBI.com to your On-Prem DataJean-Pierre Riehl
--session donnée lors du SQLSaturday Madrid 2016--
PowerBI.com is a cloud-based BI platform, enabling from personal to corporate BI. But often, your data lives on-premises, on your desktop, on a shared folder or in your enterprise datawarehouse. Microsoft team built gateways to deal with that.
In this session, we will see how to connect, lively or scheduled, your dahsboards to your on-prem data. You'll learn about Personal Gateway and Enterprise Gateway. How does it work. How to configure it. How to maintain it.
Capgemini Consulting RPA: the next revolution of Corporate FunctionsUiPath
More than ever, Technology reached a tipping point in
the optimization of Corporate Functions.
Similar to robotization of production lines in the 90’s, Corporate
Functions are initiating today their robotic transformation/
revolution.
We believe Robotic Process Automation or RPA is the lever
that will take these Corporate Functions to the next level by:
• Improving employee and customer satisfaction
• Accelerating productivity gains
• Enhancing compliance
To reach these benefits, RPA must be implemented on key
Corporate Functions that include repetitive, standardized
and transactional processes and activities such as Finance,
Compliance, Treasury and Marketing.
Within these Corporate Functions, not all processes and
activities are eligible to RPA though, hence the need to select
them carefully in order to reap the maximum benefit from
RPA implementation.
An additional RPA key success factor consists of paying a
particular attention to design an appropriate implementation
journey sticking to company specifics.
“not only SQL.”
NoSQL databases are databases store data in a format other than relational tables.
NoSQL databases or non-relational databases don’t store relationship data well.
The Business Case for Robotic Process Automation (RPA)Joe Tawfik
This paper by Kinetic Consulting Services (www.kineticcs.com) outlines the business case for Robotic Process Automation (RPA). It examines the commercial and strategic aspects of RPA.
Rpa ai automation webinar by new, cfgi, ui path 11 82018Bob Fitzpatrick
Automation…RPA…AI…Bots… are currently the hottest words across the various industries. So what do they mean and how to leverage this new technology? Join us as we explore starting an automation journey and leveraging automation in finance led by Sebastian, Bob, Andres, and Daniel. Our special guest is Boris Krumrey, UiPath’s Chief Robotics Officer, who will share with us the exciting landscape of automation and where it is heading.
Intelligent Document Processing (IDP) is a next-generation solution for extracting data from complex, unstructured documents. Unlike the technologies that came before it, IDP can handle document complexity and variation with the help of multiple AI technologies and machine learning.
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Edureka!
This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial:
1. What Is The Need For BI?
2. What Is Data Warehousing?
3. Key Terminologies Related To Data Warehouse Architecture:
a. OLTP Vs OLAP
b. ETL
c. Data Mart
d. Metadata
4. Data Warehouse Architecture
5. Demo: Creating A Data Warehouse
This introductory level talk is about Apache Flink: a multi-purpose Big Data analytics framework leading a movement towards the unification of batch and stream processing in the open source.
With the many technical innovations it brings along with its unique vision and philosophy, it is considered the 4 G (4th Generation) of Big Data Analytics frameworks providing the only hybrid (Real-Time Streaming + Batch) open source distributed data processing engine supporting many use cases: batch, streaming, relational queries, machine learning and graph processing.
In this talk, you will learn about:
1. What is Apache Flink stack and how it fits into the Big Data ecosystem?
2. How Apache Flink integrates with Hadoop and other open source tools for data input and output as well as deployment?
3. Why Apache Flink is an alternative to Apache Hadoop MapReduce, Apache Storm and Apache Spark.
4. Who is using Apache Flink?
5. Where to learn more about Apache Flink?
Nubank embraces company-wide data usage as an important competitive advantage.
In this presentation I give an overview of our current data infrastructure, how we create ETL jobs, what data tools we use and which internal services are provided by the data team.
This was originally presented on the São Paulo Machine Learning Meetup, December 2018; the deck is in english
Oracle Analytics Cloud: connect; prepare; explore; share. Liberate all data and connect to more than 50 different data sources. Powerful tools for auditable and traceable data blending, wrangling, cleansing, & modeling. Intuitive and rich exploration with self-service data visualization. Build collective intelligence by collaborating with peers and socialize insights across the organization or the world.
A Data Lake is a storage repository that can store large amount of structured, semi-structured, and unstructured data. It is a place to store every type of data in its native format with no fixed limits on account size or file. It offers high data quantity to increase analytic performance and native integration.
Data Lake is like a large container which is very similar to real lake and rivers. Just like in a lake you have multiple tributaries coming in, a data lake has structured data, unstructured data, machine to machine, logs flowing through in real-time.
Introduction To UiPath | RPA Tutorial For Beginners | RPA Training using Uipa...Edureka!
***** RPA Training using UiPath: https://www.edureka.co/robotic-process-automation-training *****
This Edureka tutorial on Introduction to UiPath will give you the fundamental knowledge about the most popular RPA tool - UiPath. Below are the topics covered in this tutorial:
1. What is RPA
2. RPA Tools
3. Introduction to UiPath
4. How to Install UiPath
5. UiPath Project Types
6. UiPath Components.
7. UiPath Demo
Extracting value from Big Data is not easy. The field of technologies and vendors is fragmented and rapidly evolving. End-to-end, general purpose solutions that work out of the box don’t exist yet, and Hadoop is no exception. And most companies lack Big Data specialists. The key to unlocking real value lies with thinking smart and hard about the business requirements for a Big Data solution. There is a long list of crucial questions to think about. Is Hadoop really the best solution for all Big Data needs? Should companies run a Hadoop cluster on expensive enterprise-grade storage, or use cheap commodity servers? Should the chosen infrastructure be bare metal or virtualized? The picture becomes even more confusing at the analysis and visualization layer. The answer to Big Data ROI lies somewhere between the herd and nerd mentality. Thinking hard and being smart about each use case as early as possible avoids costly mistakes in choosing hardware and software. This talk will illustrate how Deutsche Telekom follows this segmentation approach to make sure every individual use case drives architecture design and the selection of technologies and vendors.
Hadoop and the Data Warehouse: Point/Counter PointInside Analysis
Robin Bloor and Teradata
Live Webcast on April 22, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=2e69345c0a6a4e5a8de6fc72652e3bc6
Can you replace the data warehouse with Hadoop? Is Hadoop an ideal ETL subsystem? And what is the real magic of Hadoop? Everyone is looking to capitalize on the insights that lie in the vast pools of big data. Generating the value of that data relies heavily on several factors, especially choosing the right solution for the right context. With so many options out there, how do organizations best integrate these new big data solutions with the existing data warehouse environment?
Register for this episode of The Briefing Room to hear veteran analyst Dr. Robin Bloor as he explains where Hadoop fits into the information ecosystem. He’ll be briefed by Dan Graham of Teradata, who will offer perspective on how Hadoop can play a critical role in the analytic architecture. Bloor and Graham will interactively discuss big data in the big picture of the data center and will also seek to dispel several common misconceptions about Hadoop.
Visit InsideAnlaysis.com for more information.
Gateways to Power BI, Connect PowerBI.com to your On-Prem DataJean-Pierre Riehl
--session donnée lors du SQLSaturday Madrid 2016--
PowerBI.com is a cloud-based BI platform, enabling from personal to corporate BI. But often, your data lives on-premises, on your desktop, on a shared folder or in your enterprise datawarehouse. Microsoft team built gateways to deal with that.
In this session, we will see how to connect, lively or scheduled, your dahsboards to your on-prem data. You'll learn about Personal Gateway and Enterprise Gateway. How does it work. How to configure it. How to maintain it.
Capgemini Consulting RPA: the next revolution of Corporate FunctionsUiPath
More than ever, Technology reached a tipping point in
the optimization of Corporate Functions.
Similar to robotization of production lines in the 90’s, Corporate
Functions are initiating today their robotic transformation/
revolution.
We believe Robotic Process Automation or RPA is the lever
that will take these Corporate Functions to the next level by:
• Improving employee and customer satisfaction
• Accelerating productivity gains
• Enhancing compliance
To reach these benefits, RPA must be implemented on key
Corporate Functions that include repetitive, standardized
and transactional processes and activities such as Finance,
Compliance, Treasury and Marketing.
Within these Corporate Functions, not all processes and
activities are eligible to RPA though, hence the need to select
them carefully in order to reap the maximum benefit from
RPA implementation.
An additional RPA key success factor consists of paying a
particular attention to design an appropriate implementation
journey sticking to company specifics.
“not only SQL.”
NoSQL databases are databases store data in a format other than relational tables.
NoSQL databases or non-relational databases don’t store relationship data well.
The Business Case for Robotic Process Automation (RPA)Joe Tawfik
This paper by Kinetic Consulting Services (www.kineticcs.com) outlines the business case for Robotic Process Automation (RPA). It examines the commercial and strategic aspects of RPA.
Rpa ai automation webinar by new, cfgi, ui path 11 82018Bob Fitzpatrick
Automation…RPA…AI…Bots… are currently the hottest words across the various industries. So what do they mean and how to leverage this new technology? Join us as we explore starting an automation journey and leveraging automation in finance led by Sebastian, Bob, Andres, and Daniel. Our special guest is Boris Krumrey, UiPath’s Chief Robotics Officer, who will share with us the exciting landscape of automation and where it is heading.
Intelligent Document Processing (IDP) is a next-generation solution for extracting data from complex, unstructured documents. Unlike the technologies that came before it, IDP can handle document complexity and variation with the help of multiple AI technologies and machine learning.
Data Warehouse Tutorial For Beginners | Data Warehouse Concepts | Data Wareho...Edureka!
This Data Warehouse Tutorial For Beginners will give you an introduction to data warehousing and business intelligence. You will be able to understand basic data warehouse concepts with examples. The following topics have been covered in this tutorial:
1. What Is The Need For BI?
2. What Is Data Warehousing?
3. Key Terminologies Related To Data Warehouse Architecture:
a. OLTP Vs OLAP
b. ETL
c. Data Mart
d. Metadata
4. Data Warehouse Architecture
5. Demo: Creating A Data Warehouse
This introductory level talk is about Apache Flink: a multi-purpose Big Data analytics framework leading a movement towards the unification of batch and stream processing in the open source.
With the many technical innovations it brings along with its unique vision and philosophy, it is considered the 4 G (4th Generation) of Big Data Analytics frameworks providing the only hybrid (Real-Time Streaming + Batch) open source distributed data processing engine supporting many use cases: batch, streaming, relational queries, machine learning and graph processing.
In this talk, you will learn about:
1. What is Apache Flink stack and how it fits into the Big Data ecosystem?
2. How Apache Flink integrates with Hadoop and other open source tools for data input and output as well as deployment?
3. Why Apache Flink is an alternative to Apache Hadoop MapReduce, Apache Storm and Apache Spark.
4. Who is using Apache Flink?
5. Where to learn more about Apache Flink?
Nubank embraces company-wide data usage as an important competitive advantage.
In this presentation I give an overview of our current data infrastructure, how we create ETL jobs, what data tools we use and which internal services are provided by the data team.
This was originally presented on the São Paulo Machine Learning Meetup, December 2018; the deck is in english
Oracle Analytics Cloud: connect; prepare; explore; share. Liberate all data and connect to more than 50 different data sources. Powerful tools for auditable and traceable data blending, wrangling, cleansing, & modeling. Intuitive and rich exploration with self-service data visualization. Build collective intelligence by collaborating with peers and socialize insights across the organization or the world.
A Data Lake is a storage repository that can store large amount of structured, semi-structured, and unstructured data. It is a place to store every type of data in its native format with no fixed limits on account size or file. It offers high data quantity to increase analytic performance and native integration.
Data Lake is like a large container which is very similar to real lake and rivers. Just like in a lake you have multiple tributaries coming in, a data lake has structured data, unstructured data, machine to machine, logs flowing through in real-time.
Introduction To UiPath | RPA Tutorial For Beginners | RPA Training using Uipa...Edureka!
***** RPA Training using UiPath: https://www.edureka.co/robotic-process-automation-training *****
This Edureka tutorial on Introduction to UiPath will give you the fundamental knowledge about the most popular RPA tool - UiPath. Below are the topics covered in this tutorial:
1. What is RPA
2. RPA Tools
3. Introduction to UiPath
4. How to Install UiPath
5. UiPath Project Types
6. UiPath Components.
7. UiPath Demo
Extracting value from Big Data is not easy. The field of technologies and vendors is fragmented and rapidly evolving. End-to-end, general purpose solutions that work out of the box don’t exist yet, and Hadoop is no exception. And most companies lack Big Data specialists. The key to unlocking real value lies with thinking smart and hard about the business requirements for a Big Data solution. There is a long list of crucial questions to think about. Is Hadoop really the best solution for all Big Data needs? Should companies run a Hadoop cluster on expensive enterprise-grade storage, or use cheap commodity servers? Should the chosen infrastructure be bare metal or virtualized? The picture becomes even more confusing at the analysis and visualization layer. The answer to Big Data ROI lies somewhere between the herd and nerd mentality. Thinking hard and being smart about each use case as early as possible avoids costly mistakes in choosing hardware and software. This talk will illustrate how Deutsche Telekom follows this segmentation approach to make sure every individual use case drives architecture design and the selection of technologies and vendors.
Hadoop and the Data Warehouse: Point/Counter PointInside Analysis
Robin Bloor and Teradata
Live Webcast on April 22, 2014
Watch the archive:
https://bloorgroup.webex.com/bloorgroup/lsr.php?RCID=2e69345c0a6a4e5a8de6fc72652e3bc6
Can you replace the data warehouse with Hadoop? Is Hadoop an ideal ETL subsystem? And what is the real magic of Hadoop? Everyone is looking to capitalize on the insights that lie in the vast pools of big data. Generating the value of that data relies heavily on several factors, especially choosing the right solution for the right context. With so many options out there, how do organizations best integrate these new big data solutions with the existing data warehouse environment?
Register for this episode of The Briefing Room to hear veteran analyst Dr. Robin Bloor as he explains where Hadoop fits into the information ecosystem. He’ll be briefed by Dan Graham of Teradata, who will offer perspective on how Hadoop can play a critical role in the analytic architecture. Bloor and Graham will interactively discuss big data in the big picture of the data center and will also seek to dispel several common misconceptions about Hadoop.
Visit InsideAnlaysis.com for more information.
Every second of every day you hear about Electronic systems creating ever increasing quantities of data. Systems in markets such as finance, media, healthcare, government and scientific research feature strongly in the Big Data processing conversation. While extracting business value from Big Data is forecast to bring customer and competitive advantage and benefits. In this session hear Vas Kapsalis, NetApp Big Data Business Development Manager, discuss his views and experience on the wider world of Big Data.
The next generation user experience should move to customer engagement zones along their preferred channels with desired action to outcome approaches. With scores of information ranging from inventory to inquiry, weather to warehouse alerts, product to promotion info at disposal, enterprise digitization can create value at every customer touch point. Attendees witnessed the manifestation of TCS’ Thought Leadership in the Game of Retail.
Exploring the Wider World of Big Data- Vasalis KapsalisNetAppUK
Every second of every day you hear about Electronic systems creating ever increasing quantities of data. Systems in markets such as finance, media, healthcare, government and scientific research feature strongly in the Big Data processing conversation. While extracting business value from Big Data is forecast to bring customer and competitive advantage and benefits. In this session hear Vas Kapsalis, NetApp Big Data Business Development Manager, discuss his views and experience on the wider world of Big Data.
Customer value analysis of big data productsVikas Sardana
Business value analysis through Customer Value Model for software technology choices with a case study from Mobile Advertising industry for Big Data use case.
When Databases Meet Big data and Hadoop - Uni of Tromso Online LectureIrfan Elahi
Slides of my online lecture that I delivered to the grad students of University of Tromsø (Norway) about
"When Databases Meet Big Data - Expectations, Challenges and Opportunities"
on 13/09/2018.
The lecture provided an overview of what databases have been used for traditionally and with the rise of big data paradigms, what expectations do enterprises and organizations have now from them. With the shift from vertical scaling to horizontal scaling, what challenges germinate in the context of functional capabilities of databases and how does it all align with the expectations from big data platforms which are increasingly being considered for use-cases like ETL offloading and scalable data warehousing. Lastly, what opportunities lie in this niche and what lies beyond.
Are you confused by Big Data? Get in touch with this new "black gold" and familiarize yourself with undiscovered insights through our complimentary introductory lesson on Big Data and Hadoop!
The Practice of Big Data - The Hadoop ecosystem explained with usage scenarioskcmallu
What's the origin of Big Data? What are the real life usage scenarios where Hadoop has been successfully adopted? How do you get started within your organizations?
Hitachi Data Systems Hadoop Solution. Customers are seeing exponential growth of unstructured data from their social media websites to operational sources. Their enterprise data warehouses are not designed to handle such high volumes and varieties of data. Hadoop, the latest software platform that scales to process massive volumes of unstructured and semi-structured data by distributing the workload through clusters of servers, is giving customers new option to tackle data growth and deploy big data analysis to help better understand their business. Hitachi Data Systems is launching its latest Hadoop reference architecture, which is pre-tested with Cloudera Hadoop distribution to provide a faster time to market for customers deploying Hadoop applications. HDS, Cloudera and Hitachi Consulting will present together and explain how to get you there. Attend this WebTech and learn how to: Solve big-data problems with Hadoop. Deploy Hadoop in your data warehouse environment to better manage your unstructured and structured data. Implement Hadoop using HDS Hadoop reference architecture. For more information on Hitachi Data Systems Hadoop Solution please read our blog: http://blogs.hds.com/hdsblog/2012/07/a-series-on-hadoop-architecture.html
Creating a Next-Generation Big Data ArchitecturePerficient, Inc.
If you’ve spent time investigating Big Data, you quickly realize that the issues surrounding Big Data are often complex to analyze and solve. The sheer volume, velocity and variety changes the way we think about data – including how enterprises approach data architecture.
Significant reduction in costs for processing, managing, and storing data, combined with the need for business agility and analytics, requires CIOs and enterprise architects to rethink their enterprise data architecture and develop a next-generation approach to solve the complexities of Big Data.
Creating the data architecture while integrating Big Data into the heart of the enterprise data architecture is a challenge. This webinar covered:
-Why Big Data capabilities must be strategically integrated into an enterprise’s data architecture
-How a next-generation architecture can be conceptualized
-The key components to a robust next generation architecture
-How to incrementally transition to a next generation data architecture
Glimpse of advantage, limitations of Hadoop and Goals / Business benefits of Data Warehouse and few use cases where Hadoop can be used to strengthen Enterprise Data Warehouse of any organization.
Financial Services Expertise in Business Applications Services, Product Engineering, Applications Testing and Professional Services for Retail Banking, Capital Markets, Credit Services and Insurance
Xoriant Smartphone Application Accelerator, a set of libraries help in speeding the application development on various Smartphone platforms. Using the accelerator libraries, any application features can be incorporated in 20-50% less time than what it would take to develop from scratch. Additionally since some of the underlying foundation has already been tested, the application quality is also significantly higher. The Xoriant Smartphone Accelerator libraries are available for iPhone, Android, Nokia – QT, Blackberry and Windows Mobile.
Understand the challenges of programming application for each mobile platform and Xoriant’s recommendations of porting your mobile apps for overcoming this challenge. Also learn more on why mobile testing is an integral part of a mobile app development project which incorporates testing applications across devices, networks and carriers.
SEP Webinar –HTML5: The GenX Technology for building scalable and high perfor...Xoriant Corporation
In this Webinar, you’ll learn- 1. basic concepts of HTML5, 2. a comparison of HTML5 features with Flash/Flex, Silverlight and Java/JavaFX, 3. a new communication protocol called WebSocket, and 4. use cases where HTML5 and cloud computing have combined to deliver cost-effective and compelling enterprise applications.
Learn SQL from basic queries to Advance queriesmanishkhaire30
Dive into the world of data analysis with our comprehensive guide on mastering SQL! This presentation offers a practical approach to learning SQL, focusing on real-world applications and hands-on practice. Whether you're a beginner or looking to sharpen your skills, this guide provides the tools you need to extract, analyze, and interpret data effectively.
Key Highlights:
Foundations of SQL: Understand the basics of SQL, including data retrieval, filtering, and aggregation.
Advanced Queries: Learn to craft complex queries to uncover deep insights from your data.
Data Trends and Patterns: Discover how to identify and interpret trends and patterns in your datasets.
Practical Examples: Follow step-by-step examples to apply SQL techniques in real-world scenarios.
Actionable Insights: Gain the skills to derive actionable insights that drive informed decision-making.
Join us on this journey to enhance your data analysis capabilities and unlock the full potential of SQL. Perfect for data enthusiasts, analysts, and anyone eager to harness the power of data!
#DataAnalysis #SQL #LearningSQL #DataInsights #DataScience #Analytics
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
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Discussion on Vector Databases, Unstructured Data and AI
https://www.meetup.com/unstructured-data-meetup-new-york/
This meetup is for people working in unstructured data. Speakers will come present about related topics such as vector databases, LLMs, and managing data at scale. The intended audience of this group includes roles like machine learning engineers, data scientists, data engineers, software engineers, and PMs.This meetup was formerly Milvus Meetup, and is sponsored by Zilliz maintainers of Milvus.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
2. Agenda Big Data Challenges Big Data Analytics Industry Trends Hadoop as a Solution Real Life Solution Studies
•Case Study I - Retail Industry
•Case Study II - Online Advertising Industry How Xoriant can help? Q & A
4. Traditional Approach & Its Limitations
Data Warehousing Vendors (ETL)
Costs - High Initial Setup,
Maintenance, Subscription
or Licensing Fees
No support for
unstructured data
Multiple copies of data in different formats
Data latency and
bottlenecks
No support for ad-hoc query
Note: The Logos are proprietary of the individual companies
5. Big Data and Analytics - Trends
Enterprise Data Hub or Data Lake (Hadoop with HDFS)
Commodity Hardware
No multiple data copies
Fault-Tolerant storage for Raw data As-Is
Current Limitations - Write/Append only, No Delete or Update
Unified Data Access
Multiple Data Processing Paradigms
In-memory processing
In-memory,
Real-time Stream processing
Analytics based on Distributed SQL Processing
Falling hardware prices
Batch mode processing for data size more than Hundreds of TBs
In-memory processing for data size less than hundreds of TBs
ETL Trends
Data
Processing
Trends
Architecture
Trends
Open Source Software
6. Hadoop Proposition
Open Source Ecosystem
No data loss through replicated storage (HDFS)
Runs on commodity hardware
•Map-Reduce
•Script based (Pig Latin)
•SQL like - HiveQL, Apache Drill, Presto (Facebook)
•Impala (Cloudera), HAWQ (Pivotal)
•In-memory processing (Apache Spark)
Multiple data analysis/processing paradigms
9. Case Study - 1
Benefits
Retail Industry
Problem Scenario
Personalize marketing campaigns, coupons, offers, marking down inventories
Improving customer loyalty – leads to sales and profitability
Competition from other retailers
ETL based analysis tasks - taking lot of time – up to 6 weeks
Software systems (Oracle, Greenplum, SAS, Teradata)
Mainframe based expensive hardware systems
Hadoop based Solution
Data stored into HDFS with replication
300 Hadoop nodes with 2PB data
Data processing time down to 1 week and even daily
Mainframe cost savings
No software licensing costs
Limitless data storage with HDFS
No multiple data copies
Low cost
10. Case Study - 2
Benefits
Attribution computation time down to 45 minutes
Capable of processing up to 300GB data for each computation
Manageable data storage with HDFS
Low cost
Online Advertising Industry (Attribution Computation)
Problem Scenario
Growing Ads Impression and conversion events
Longer attribution computation time (6 to 8 hours for each computation run). Advertisers needed quick results
Unable to process more than 150GB data within each computation
IBM Netezza based solution along with Oracle
Expensive hardware and software costs
Hadoop based Solution
Data stored into HDFS with replication
Initially used HiveQL then moved to Cloudera Impala (MPP architecture based Distributed SQL Engine)
11. Xoriant Big Data Practice - Overview Understands technological needs and organizational challenges faced with respect to Big Data Understands rapidly evolving Big Data technology space Can help bridge the gaps with Big Data capabilities Brings Big Data and NoSQL technology expertise
12. Xoriant – Big Data Center of Excellence
Email: bigdata@xoriant.com
For FREE consultation, please contact us on the above mentioned email address.
Do you have any Questions?