It's a very simple representation of how the benefits of Analytics can affect the business growth, even though the business is performing without it.
See my other articles attached in my profile as well.
"Planning Your Analytics Implementation" by Bachtiar Rifai (Kofera Technology)Tech in Asia ID
Bachtiar is a tech startup & science enthusiast with more than 7 years experience in digital marketing, ecommerce, analytics and product development. Bachtiar has spend his career life as marketing leader at top ecommerce such as Lazada & Blanja.com. Currently Bachtiar develop a startup called Kofera, a technology company who provides Software as a Service (SaaS) marketing automation platform powered by Artificial Intelligence (AI) and machine learning. Established in 2016, Kofera helps companies build & optimize PPC campaign using machine learning algorithm to maximize business ROI. Kofera has helped many clients from various industries. Recently, Kofera received pra-series A funding lead by MDI Ventures and followed by Indosterling, DNC & Gunung Sewu.
***
This slide was shared at Tech in Asia Product Development Conference 2017 (PDC'17) on 9-10 August 2017.
Get more insightful updates from TIA by subscribing techin.asia/updateselalu
Panelists from a large company, a small company and a software consulting firm will share insights on how their companies are tackling the arena of Big Data and how to leverage a variety of data sources for strategic decision-making.
"Planning Your Analytics Implementation" by Bachtiar Rifai (Kofera Technology)Tech in Asia ID
Bachtiar is a tech startup & science enthusiast with more than 7 years experience in digital marketing, ecommerce, analytics and product development. Bachtiar has spend his career life as marketing leader at top ecommerce such as Lazada & Blanja.com. Currently Bachtiar develop a startup called Kofera, a technology company who provides Software as a Service (SaaS) marketing automation platform powered by Artificial Intelligence (AI) and machine learning. Established in 2016, Kofera helps companies build & optimize PPC campaign using machine learning algorithm to maximize business ROI. Kofera has helped many clients from various industries. Recently, Kofera received pra-series A funding lead by MDI Ventures and followed by Indosterling, DNC & Gunung Sewu.
***
This slide was shared at Tech in Asia Product Development Conference 2017 (PDC'17) on 9-10 August 2017.
Get more insightful updates from TIA by subscribing techin.asia/updateselalu
Panelists from a large company, a small company and a software consulting firm will share insights on how their companies are tackling the arena of Big Data and how to leverage a variety of data sources for strategic decision-making.
"Data Informed vs Data Driven" by Casper Sermsuksan (Kulina)Tech in Asia ID
Casper is currently the Head of Product & Growth at Kulina, an online food subscription service in Jakarta. Casper is responsible for driving product management and growth initiatives as well as leading marketing efforts. Previously, he led the product marketing teams at Product Madness in San Francisco. During his tenure at Product Madness, he helped the company's top app, Heart of Vegas achieve the record of $200M in annual revenue. Outside of his day-to-day work, he advises corporations and startups on product and growth, and writes frequently on Startup Grind, Mind the Product & Muzli. He graduated with a business degree from the University of Southern California in Los Angeles.
***
This slide was shared at Tech in Asia Product Development Conference 2017 (PDC'17) on 9-10 August 2017.
Get more insightful updates from TIA by subscribing techin.asia/updateselalu
Ron Bodkin, Founder and President of Think Big, a Teradata company, discussed how big data can give an organization a competitive advantage over its rivals during his presentation at the 2014 Chief Information Officer Leadership Forum in San Francisco on Oct. 28. In his presentation, Bodkin noted big data can be an asset for an organization, but only if an organization understands how to use it.
Today’s organizations often view data as part of either a “swamp” or a “reservoir,” Bodkin said. There is a lot of data that is readily available to organizations, Bodkin said, but those who merely keep it on hand without learning about its value could struggle. Instead, Bodkin noted organizations need to know how to implement data links properly to ensure that they can optimize their value: “I think it’s worth saying in implementing data links … we tend to see [mistakes] that we see a lot of organizations making that hold them back from achieving the potential.”
In addition, a cultural change is taking place in many organizations, Bodkin said, which is leading more organizations to focus on finding ways to get the most out of their data. Organizations that closely examine their internal data processes can take the necessary steps to ensure they can collect data and use it properly: “Even getting the technologies in place is just a starting point; they need to get adopted, they need to get integrated into people’s workforce and need to start to enable people to be successful with certain [measurements on] how they’re using them.”
- See more at: http://www.argylejournal.com/chief-information-officer/2014-chief-information-officer-leadership-forum-ron-bodkin-founder-and-president-think-big-a-teradata-company/#sthash.tETQQpz8.dpuf
Operationalizing Data Science: The Right Architecture and ToolsVMware Tanzu
In part one of this two-part series, you learned some of the common reasons enterprises struggle to turn insights into actions as well as a strategy for overcoming these challenges to successfully operationalize data science. In part two, it’s time to fill in the architectural and technological details of that strategy.
Pivotal Data Scientist Megha Agarwal will share the key ingredients to successfully put data science models in production and use them to drive actions in real-time. In this webinar, you will learn:
- Adopting extreme programming practices for data science
- Importance of working in a balanced team
- How to put and maintain machine learning models in production
- End-to-end pipeline design
Presenter: Megha Agarwal, Data Scientist
Five Pitfalls when Operationalizing Data Science and a Strategy for SuccessVMware Tanzu
Enterprise executives and IT teams alike know that data science is not optional, but struggle to benefit from it because the process takes too long and operationalizing models in applications can be hairy.
Join guest speaker, Forrester Research’s Mike Gualtieri and Pivotal’s Jeff Kelly and Dormain Drewitz for an interactive discussion about operationalizing data science in your business. In this webinar, the first of a two-part series, you will learn:
- The essential value of data science and the concept of perishable insights.
- Five common pitfalls of data science teams.
- How to dramatically increase the productivity of data scientists.
- The smooth hand-off steps required to operationalize data science models in enterprise applications.
Presenter : Guest Speakers Mike Gualtieri, Forrester, Dormain Drewitz and Jeff Kelly, Pivotal
Iain Curtain, Edgewater Ranzal senior consultant, presented "Delivering Actionable Insight - Using Visualization and Perception Techniques to Enhance User Understanding" at KScope14.
Beginner’s Primer on Business Intelligence
Business Intelligence is a set of process, architecture, technologies that converts the raw data into meaningful information which helps any business in making productive decision.
Business Intelligence directly affects the strategic and progressive decisions of any organization by making the use of historical data and facts. It also helps in analysing the data and explains the end users the nature of the business in the form of Reports, Graphs and Dashboards.
The session will cover the following topics:
-What is Business Intelligence
-Where does BI fit within an organization
-Advantages of BI systems
-Various types of BI users
-Various BI Tools
-Careers in BI
-Q & A
Follow Us For More Updates
Facebook Page https://www.facebook.com/CLTConsultin...
LinkedIn Page http://linkedin.com/company/cltcsi
Twitter Page https://twitter.com/CLTCSGLOBAL
YouTube Page https://www.youtube.com/channel/UCzqO...
Instagram Page https://www.instagram.com/clt_consult...
#businessintelligence #bi #bitool #oraclebi #otbi #oracle #cltconsulting
How the information or the data is handled? Which medium is used to handle it? Or how the data is processed and stored? This is where the term Big Data Analytics comes to play.
https://www.pelotongroup.com/services/big-data-analytics/
Big Data LDN 2018: FIGHTING DATA CHAOS: CONNECTING USERS TO DATA AT SCALEMatt Stubbs
Date: 13th November 2018
Location: Self-Service Analytics
Theatre Time: 12:30 - 13:00
Speaker: Joel McKelvey
Organisation: Looker
About: Companies that use data well are more efficient, effective, and profitable. Unfortunately, most organizations struggle to keep up with the changing supply of data — and the growing business demands for that data. The key is to connect data supply to data users in a way that scales, supports existing workflows, and serves as a foundation for the future.
This session will explore how to bring data to users where and when they need it without sacrificing data governance or unified metrics. This session will also present proven ways to build a data foundation for your organisation that can support future changes in both data supply and data demand.
Specifically, attendees will discover:
• The key considerations to driving the most value from data, including: self-service, governance, custom interfaces, modeling, and connections to existing business systems.
• How to provide users access to data in a way that naturally fits in their existing workflows and allows users to take immediate action.
• How companies like Deliveroo and King extract critical business insights from growing data and deliver those insights to their business users.
Search Driven Analytics - A New Approach for Data DiscoveryRoosboard
Search to analyze your data (https://roosboard.com/)and generate a report immediately with the search-based dashboard.To know more about search analytic dashboard visit the above slides.
What is this ‘Big Data’?
Introduction and Key words
Any secrets behind big data?
The 4V’s of Big Data
Big Data Analytics
What to do with this data?
Usefulness of Business Intelligence (BI)
It’s critical for organizations to formalize their approaches to maintaining and improving capabilities. The key is to use structured, objective third-party diagnostics that use a valid competency model coupled with manager assessments and self-assessments.
"Data Informed vs Data Driven" by Casper Sermsuksan (Kulina)Tech in Asia ID
Casper is currently the Head of Product & Growth at Kulina, an online food subscription service in Jakarta. Casper is responsible for driving product management and growth initiatives as well as leading marketing efforts. Previously, he led the product marketing teams at Product Madness in San Francisco. During his tenure at Product Madness, he helped the company's top app, Heart of Vegas achieve the record of $200M in annual revenue. Outside of his day-to-day work, he advises corporations and startups on product and growth, and writes frequently on Startup Grind, Mind the Product & Muzli. He graduated with a business degree from the University of Southern California in Los Angeles.
***
This slide was shared at Tech in Asia Product Development Conference 2017 (PDC'17) on 9-10 August 2017.
Get more insightful updates from TIA by subscribing techin.asia/updateselalu
Ron Bodkin, Founder and President of Think Big, a Teradata company, discussed how big data can give an organization a competitive advantage over its rivals during his presentation at the 2014 Chief Information Officer Leadership Forum in San Francisco on Oct. 28. In his presentation, Bodkin noted big data can be an asset for an organization, but only if an organization understands how to use it.
Today’s organizations often view data as part of either a “swamp” or a “reservoir,” Bodkin said. There is a lot of data that is readily available to organizations, Bodkin said, but those who merely keep it on hand without learning about its value could struggle. Instead, Bodkin noted organizations need to know how to implement data links properly to ensure that they can optimize their value: “I think it’s worth saying in implementing data links … we tend to see [mistakes] that we see a lot of organizations making that hold them back from achieving the potential.”
In addition, a cultural change is taking place in many organizations, Bodkin said, which is leading more organizations to focus on finding ways to get the most out of their data. Organizations that closely examine their internal data processes can take the necessary steps to ensure they can collect data and use it properly: “Even getting the technologies in place is just a starting point; they need to get adopted, they need to get integrated into people’s workforce and need to start to enable people to be successful with certain [measurements on] how they’re using them.”
- See more at: http://www.argylejournal.com/chief-information-officer/2014-chief-information-officer-leadership-forum-ron-bodkin-founder-and-president-think-big-a-teradata-company/#sthash.tETQQpz8.dpuf
Operationalizing Data Science: The Right Architecture and ToolsVMware Tanzu
In part one of this two-part series, you learned some of the common reasons enterprises struggle to turn insights into actions as well as a strategy for overcoming these challenges to successfully operationalize data science. In part two, it’s time to fill in the architectural and technological details of that strategy.
Pivotal Data Scientist Megha Agarwal will share the key ingredients to successfully put data science models in production and use them to drive actions in real-time. In this webinar, you will learn:
- Adopting extreme programming practices for data science
- Importance of working in a balanced team
- How to put and maintain machine learning models in production
- End-to-end pipeline design
Presenter: Megha Agarwal, Data Scientist
Five Pitfalls when Operationalizing Data Science and a Strategy for SuccessVMware Tanzu
Enterprise executives and IT teams alike know that data science is not optional, but struggle to benefit from it because the process takes too long and operationalizing models in applications can be hairy.
Join guest speaker, Forrester Research’s Mike Gualtieri and Pivotal’s Jeff Kelly and Dormain Drewitz for an interactive discussion about operationalizing data science in your business. In this webinar, the first of a two-part series, you will learn:
- The essential value of data science and the concept of perishable insights.
- Five common pitfalls of data science teams.
- How to dramatically increase the productivity of data scientists.
- The smooth hand-off steps required to operationalize data science models in enterprise applications.
Presenter : Guest Speakers Mike Gualtieri, Forrester, Dormain Drewitz and Jeff Kelly, Pivotal
Iain Curtain, Edgewater Ranzal senior consultant, presented "Delivering Actionable Insight - Using Visualization and Perception Techniques to Enhance User Understanding" at KScope14.
Beginner’s Primer on Business Intelligence
Business Intelligence is a set of process, architecture, technologies that converts the raw data into meaningful information which helps any business in making productive decision.
Business Intelligence directly affects the strategic and progressive decisions of any organization by making the use of historical data and facts. It also helps in analysing the data and explains the end users the nature of the business in the form of Reports, Graphs and Dashboards.
The session will cover the following topics:
-What is Business Intelligence
-Where does BI fit within an organization
-Advantages of BI systems
-Various types of BI users
-Various BI Tools
-Careers in BI
-Q & A
Follow Us For More Updates
Facebook Page https://www.facebook.com/CLTConsultin...
LinkedIn Page http://linkedin.com/company/cltcsi
Twitter Page https://twitter.com/CLTCSGLOBAL
YouTube Page https://www.youtube.com/channel/UCzqO...
Instagram Page https://www.instagram.com/clt_consult...
#businessintelligence #bi #bitool #oraclebi #otbi #oracle #cltconsulting
How the information or the data is handled? Which medium is used to handle it? Or how the data is processed and stored? This is where the term Big Data Analytics comes to play.
https://www.pelotongroup.com/services/big-data-analytics/
Big Data LDN 2018: FIGHTING DATA CHAOS: CONNECTING USERS TO DATA AT SCALEMatt Stubbs
Date: 13th November 2018
Location: Self-Service Analytics
Theatre Time: 12:30 - 13:00
Speaker: Joel McKelvey
Organisation: Looker
About: Companies that use data well are more efficient, effective, and profitable. Unfortunately, most organizations struggle to keep up with the changing supply of data — and the growing business demands for that data. The key is to connect data supply to data users in a way that scales, supports existing workflows, and serves as a foundation for the future.
This session will explore how to bring data to users where and when they need it without sacrificing data governance or unified metrics. This session will also present proven ways to build a data foundation for your organisation that can support future changes in both data supply and data demand.
Specifically, attendees will discover:
• The key considerations to driving the most value from data, including: self-service, governance, custom interfaces, modeling, and connections to existing business systems.
• How to provide users access to data in a way that naturally fits in their existing workflows and allows users to take immediate action.
• How companies like Deliveroo and King extract critical business insights from growing data and deliver those insights to their business users.
Search Driven Analytics - A New Approach for Data DiscoveryRoosboard
Search to analyze your data (https://roosboard.com/)and generate a report immediately with the search-based dashboard.To know more about search analytic dashboard visit the above slides.
What is this ‘Big Data’?
Introduction and Key words
Any secrets behind big data?
The 4V’s of Big Data
Big Data Analytics
What to do with this data?
Usefulness of Business Intelligence (BI)
It’s critical for organizations to formalize their approaches to maintaining and improving capabilities. The key is to use structured, objective third-party diagnostics that use a valid competency model coupled with manager assessments and self-assessments.
Collaborate 2018: How to Get Cross Functional Reporting with an Enterprise Da...Datavail
Many organizations not only lack the ability to look at their data across the organization as whole, but often have no lens into the metrics that they need to report against or manage the business of their own departments.
How beneficial would it be to have a central data information repository – we call it an Enterprise Data Warehouse – from which to retrieve accurate data from across all aspects of your business? This presentation explains how this, and more, can be a reality for your business, in a relatively short amount of time.
Stop the madness - Never doubt the quality of BI again using Data GovernanceMary Levins, PMP
Does this sound familiar? "Are you sure those numbers are right?" "Why are your numbers different than theirs?"
We've all heard it and had that gut wrenching feeling of doubt that comes with uncertainty around the quality of the numbers.
Stop the madness! Presented in Dunwoody on April 18 by industry leading expert Mary Levins who discusseses what it takes to successfully take control of your data using the Data Governance Framework. This framework is proven to improve the quality of your BI solutions.
Mary is the founder of Sierra Creek Consulting
Stuart Edwards, Principal Consultant of hut4 Data Science, shares his experiences of wrangling the broad range of data sources available to the collections industry.
Further information about this topic can be found in this article in the IMA Agent magazine:
http://www.imal.com.au/eAGENT/eagentv51i02/index.html
This is the exciting world of Data Analytics. And the good part is, it is for all.
Whether you have a small to medium enterprise or a large one, you can benefit from data analysis. Here’s how.
Data Analytics/ Business Intelligence is a method of analyzing historical data to make informed decisions and predict future results.
Its strength lies in the ability to drill down from summary data – whether it is graphed or not.
This is the exciting world of Data Analytics. And the good part is, it is for all.
Whether you have a small to medium enterprise or a large one, you can benefit from data analysis. Here’s how.
Data Analytics/ Business Intelligence is a method of analyzing historical data to make informed decisions and predict future results.
Its strength lies in the ability to drill down from summary data – whether it is graphed or not.
Analytics helps you answer questions about your business
It helps you get a bird’s eye-view of your business, across branches, businesses.
From the top-view to drill-down to the smallest detail possible.
An example would be drilling down on sales figures, starting with year, then drilling down to a particular quarter, and then to a month(s) within that quarter
Corrective actions at the right places at the right time
For more details contact:
Data Analytics/ Business Intelligence is a method of analyzing historical data to make informed decisions and predict future results.
Its strength lies in the ability to drill down from summary data – whether it is graphed or not.
Analytics helps you answer questions about your business
It helps you get a bird’s eye-view of your business, across branches, businesses.
From the top-view to drill-down to the smallest detail possible.
An example would be drilling down on sales figures, starting with year, then drilling down to a particular quarter, and then to a month(s) within that quarter
Corrective actions at the right places at the right time
Business Agility Must Be Based on a New Flexible and Agile Data ApproachDenodo
Access to full webinar: Business Agility Must Be Based on a New Flexible and Agile Data Approach (session 4) - http://goo.gl/x6fr5h
Obtaining a deeper understanding of your customers’ needs, contextual marketing, and overall business intelligence and agility, depend on accurate, timely, and relevant data. This data needs to be collected from muliple internal and external sources and subsequently combined, refined, and fueled into a diverse portfolio of business intelligence and process applications.
According to Holger Kisker Ph.D., companies today need a flexible data management architecture to cope with both traditional and emerging sources of data (in any structure), advanced data analytics to extract deeper business insights, and efficient ways to deliver these insights as information or data services for better business decisions. To achieve this, they need a data virtualization layer that makes all data available as needed.
"How To Build and Lead a Winning Data Team" by Cahyo Listyanto (Bizzy.co.id)Tech in Asia ID
Cahyo is a data geek, gamer and comic nerd.
Excel and Database are his favorite since his middle school.
Having graduated from a Vocational High School of Informatics and Technology
made him able to start his career early and led many DWH BI projects at his early 20.
He currently leading a data team in bizzy.co.id as the Head of Data Analytics.
Previously he worked for Microsoft Indonesia as Data Platform Technology Specialist where he provides strategic technical leadership supporting Microsoft customers and partners to adopt, deploy, and support solutions based on SQL Server and Data Platform related technologies.
***
This slide was shared at Tech in Asia Product Development Conference 2017 (PDC'17) on 9-10 August 2017.
Get more insightful updates from TIA by subscribing techin.asia/updateselalu
Going Beyond ‘What Success Looks Like’ – Using Data to Achieve Successful Pro...Jamie Clouting (CSPO)
Delivering value is at the heart of the Business Analyst role, but how easy is it to identify tangible value and prove the success of a project or program?
In agile projects we’ll often define a “definition of done” or ask the question “what does success look like”. At LateRooms.com, we’ve developed a toolkit for our Business Analysts to support the business in using data to define what success looks like, and track it throughout the project lifecycle.
This presentation will look at the ways LateRooms.com collects, analyses and uses data to better define the problem space, setup up KPI driven Critical Success Factors and present Benefits Realisation.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
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.
Unleashing the Power of Data_ Choosing a Trusted Analytics Platform.pdfEnterprise Wired
In this guide, we'll explore the key considerations and features to look for when choosing a Trusted analytics platform that meets your organization's needs and delivers actionable intelligence you can trust.
06-04-2024 - NYC Tech Week - Discussion on Vector Databases, Unstructured Data and AI
Round table discussion of vector databases, unstructured data, ai, big data, real-time, robots and Milvus.
A lively discussion with NJ Gen AI Meetup Lead, Prasad and Procure.FYI's Co-Found
The Building Blocks of QuestDB, a Time Series Databasejavier ramirez
Talk Delivered at Valencia Codes Meetup 2024-06.
Traditionally, databases have treated timestamps just as another data type. However, when performing real-time analytics, timestamps should be first class citizens and we need rich time semantics to get the most out of our data. We also need to deal with ever growing datasets while keeping performant, which is as fun as it sounds.
It is no wonder time-series databases are now more popular than ever before. Join me in this session to learn about the internal architecture and building blocks of QuestDB, an open source time-series database designed for speed. We will also review a history of some of the changes we have gone over the past two years to deal with late and unordered data, non-blocking writes, read-replicas, or faster batch ingestion.
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
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
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.
1. • Longer time to get the
processed data.
• Limited, fixed and standard
formats.
• Limited insight and delay.
• Looking for the missing data
takes further more time.
• Finding Upselling and Cross-
Selling takes more time.
• Limited drill-down in the
data.
• Prediction is purely based on
instinct.
Introduced BI Tool
Introduced Advanced
Analytics
• Gain new insight faster.
• Better monitoring and
decision making with large
data sets on daily basis.
• Find missing information
faster.
• Find Upselling and Cross-
Selling Opportunities.
• Improved efficiency - saving
time and money.
• Know customer behaviour.
• Find the reason of any
negatives quickly.
BusinessGrowth
Along with all the
advantages of faster and
powerful analytics, we can
now do predictions based
on various insights of the
business, and can be
prepared.
Expand the horizon for
exploring more insight
with processing Big Data
and very advanced
statistics.
Why
Analytics
and to
what level
Novoniel Deb
Using reports and Excel
charts