Big data industry 2015
•
0 likes•604 views
With the data size doubling almost every 2 years (around 9 Zeta Bytes data now exists on the internet), getting relevant, qualitative and competitive data is a regular pain for all industries across verticals. We have tried our best to help ease this data acquisition problem for various companies and will continue to do the same. Here is an infographic depicting the growth of Big Data industry and a review of the year that was 2015, for PromptCloud.
Report
Share
Report
Share
Download to read offline
Recommended
7 E-commerce Trends and Predictions for 2017
E-commerce is all set to have another record breaking year. Whilst the statisticians are counting the closing totals of 2016, we have made some predictions on E-commerce industry in 2017.
Where should you put your data scientists?
I delivered this keynote at the Fast Forward Labs Data Leadership Conference on April 28, 2016. You can find related materials in the following publications:
https://www.oreilly.com/ideas/where-should-you-put-your-data-scientists
http://firstround.com/review/doing-data-science-right-your-most-common-questions-answered/
Query Understanding: A Manifesto
Query understanding is about focusing less on the results and more on the query. It’s about figuring out what the searcher wants, rather than scoring and ranking results. Once you’ve established this mindset, your approach to search changes: you focus on query performance rather than ranking.
Presented at QConSF 2016: https://qconsf.com/sf2016/presentation/query-understanding-manifesto
What is a Data Scientist
Join our #DataTalk on Thursdays at 5 p.m. ET. This week, we tweeted with Dr. Michael Wu, the Chief Scientist at Lithium, where he applies data-driven methodologies to investigate the complex dynamics of the social web.
Michael works with big data and has developed many predictive and prescriptive social analytics with actionable insights. His R&D won him the recognition as a 2010 Influential Leader by CRM Magazine.
You can see all tweets and resources here:
http://www.experian.com/blogs/news/about/data-scientists/
Be a Data Scientist in 8 steps!
Data science is the new thing! How to be a data scientist? See here.
This was originally was written by the team behind DataCamp, - the online interactive learning platform for data science!
Titan: Big Graph Data with Cassandra
Titan is an open source distributed graph database build on top of Cassandra that can power real-time applications with thousands of concurrent users over graphs with billions of edges. Graphs are a versatile data model for capturing and analyzing rich relational structures. Graphs are an increasingly popular way to represent data in a wide range of domains such as social networking, recommendation engines, advertisement optimization, knowledge representation, health care, education, and security.
This presentation discusses Titan's data model, query language, and novel techniques in edge compression, data layout, and vertex-centric indices which facilitate the representation and processing of Big Graph Data across a Cassandra cluster. We demonstrate Titan's performance on a large scale benchmark evaluation using Twitter data.
Presented at the Cassandra 2012 Summit.
Titan: The Rise of Big Graph Data
A graph is a data structure composed of vertices/dots and edges/lines. A graph database is a software system used to persist and process graphs. The common conception in today's database community is that there is a tradeoff between the scale of data and the complexity/interlinking of data. To challenge this understanding, Aurelius has developed Titan under the liberal Apache 2 license. Titan supports both the size of modern data and the modeling power of graphs to usher in the era of Big Graph Data. Novel techniques in edge compression, data layout, and vertex-centric indices that exploit significant orders are used to facilitate the representation and processing of a single atomic graph structure across a multi-machine cluster. To ensure ease of adoption by the graph community, Titan natively implements the TinkerPop 2 Blueprints API. This presentation will review the graph landscape, Titan's techniques for scale by distribution, and a collection of satellite graph technologies to be released by Aurelius in the coming summer months of 2012.
Recommended
7 E-commerce Trends and Predictions for 2017
E-commerce is all set to have another record breaking year. Whilst the statisticians are counting the closing totals of 2016, we have made some predictions on E-commerce industry in 2017.
Where should you put your data scientists?
I delivered this keynote at the Fast Forward Labs Data Leadership Conference on April 28, 2016. You can find related materials in the following publications:
https://www.oreilly.com/ideas/where-should-you-put-your-data-scientists
http://firstround.com/review/doing-data-science-right-your-most-common-questions-answered/
Query Understanding: A Manifesto
Query understanding is about focusing less on the results and more on the query. It’s about figuring out what the searcher wants, rather than scoring and ranking results. Once you’ve established this mindset, your approach to search changes: you focus on query performance rather than ranking.
Presented at QConSF 2016: https://qconsf.com/sf2016/presentation/query-understanding-manifesto
What is a Data Scientist
Join our #DataTalk on Thursdays at 5 p.m. ET. This week, we tweeted with Dr. Michael Wu, the Chief Scientist at Lithium, where he applies data-driven methodologies to investigate the complex dynamics of the social web.
Michael works with big data and has developed many predictive and prescriptive social analytics with actionable insights. His R&D won him the recognition as a 2010 Influential Leader by CRM Magazine.
You can see all tweets and resources here:
http://www.experian.com/blogs/news/about/data-scientists/
Be a Data Scientist in 8 steps!
Data science is the new thing! How to be a data scientist? See here.
This was originally was written by the team behind DataCamp, - the online interactive learning platform for data science!
Titan: Big Graph Data with Cassandra
Titan is an open source distributed graph database build on top of Cassandra that can power real-time applications with thousands of concurrent users over graphs with billions of edges. Graphs are a versatile data model for capturing and analyzing rich relational structures. Graphs are an increasingly popular way to represent data in a wide range of domains such as social networking, recommendation engines, advertisement optimization, knowledge representation, health care, education, and security.
This presentation discusses Titan's data model, query language, and novel techniques in edge compression, data layout, and vertex-centric indices which facilitate the representation and processing of Big Graph Data across a Cassandra cluster. We demonstrate Titan's performance on a large scale benchmark evaluation using Twitter data.
Presented at the Cassandra 2012 Summit.
Titan: The Rise of Big Graph Data
A graph is a data structure composed of vertices/dots and edges/lines. A graph database is a software system used to persist and process graphs. The common conception in today's database community is that there is a tradeoff between the scale of data and the complexity/interlinking of data. To challenge this understanding, Aurelius has developed Titan under the liberal Apache 2 license. Titan supports both the size of modern data and the modeling power of graphs to usher in the era of Big Graph Data. Novel techniques in edge compression, data layout, and vertex-centric indices that exploit significant orders are used to facilitate the representation and processing of a single atomic graph structure across a multi-machine cluster. To ensure ease of adoption by the graph community, Titan natively implements the TinkerPop 2 Blueprints API. This presentation will review the graph landscape, Titan's techniques for scale by distribution, and a collection of satellite graph technologies to be released by Aurelius in the coming summer months of 2012.
Myths and Mathemagical Superpowers of Data Scientists
Some people think data scientists are mythical beings, like unicorns, or they are some sort of nouveau fad that will quickly fade. Not true, says IBM big data evangelist James Kobielus. In this engaging presentation, with artwork created by Angela Tuminello, Kobielus debunks 10 myths about data scientists and their role in analytics and big data. You might also want to read the full blog by Kobielus that spawned this presentation: "Data Scientists: Myths and Mathemagical Superpowers" - http://ibm.co/PqF7Jn
For more information, visit http://www.ibmbigdatahub.com
Introduction to R for Data Mining
We at Revolution Analytics are often asked “What is the best way to learn R?” While acknowledging that there may be as many effective learning styles as there are people we have identified three factors that greatly facilitate learning R. For a quick start:
- Find a way of orienting yourself in the open source R world
- Have a definite application area in mind
- Set an initial goal of doing something useful and then build on it
In this webinar, we focus on data mining as the application area and show how anyone with just a basic knowledge of elementary data mining techniques can become immediately productive in R. We will:
- Provide an orientation to R’s data mining resources
- Show how to use the "point and click" open source data mining GUI, rattle, to perform the basic data mining functions of exploring and visualizing data, building classification models on training data sets, and using these models to classify new data.
- Show the simple R commands to accomplish these same tasks without the GUI
- Demonstrate how to build on these fundamental skills to gain further competence in R
- Move away from using small test data sets and show with the same level of skill one could analyze some fairly large data sets with RevoScaleR
Data scientists and analysts using other statistical software as well as students who are new to data mining should come away with a plan for getting started with R.
How to Interview a Data Scientist
How To Interview a Data Scientist
Daniel Tunkelang
Presented at the O'Reilly Strata 2013 Conference
Video: https://www.youtube.com/watch?v=gUTuESHKbXI
Interviewing data scientists is hard. The tech press sporadically publishes “best” interview questions that are cringe-worthy.
At LinkedIn, we put a heavy emphasis on the ability to think through the problems we work on. For example, if someone claims expertise in machine learning, we ask them to apply it to one of our recommendation problems. And, when we test coding and algorithmic problem solving, we do it with real problems that we’ve faced in the course of our day jobs. In general, we try as hard as possible to make the interview process representative of actual work.
In this session, I’ll offer general principles and concrete examples of how to interview data scientists. I’ll also touch on the challenges of sourcing and closing top candidates.
A Statistician's View on Big Data and Data Science (Version 1)
Presentation given by Dr. Diego Kuonen, CStat PStat CSci, on November 20, 2013, at the "IBM Developer Days 2013" in Zurich, Switzerland.
ABSTRACT
There is no question that big data has hit the business, government and scientific sectors. The demand for skills in data science is unprecedented in sectors where value, competitiveness and efficiency are driven by data. However, there is plenty of misleading hype around the terms big data and data science. This presentation gives a professional statistician's view on these terms and illustrates the connection between data science and statistics.
The presentation is also available at http://www.statoo.com/BigDataDataScience/.
Enterprise Intelligence
Enterprise Intelligence: Putting the Pieces Together
http://enterpriserelevance.com/kdd2016/keynote.html
These slides are for a keynote presentation delivered at the Workshop on Enterprise Intelligence, held in conjunction with the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016).
About the author:
Daniel Tunkelang is a data science and engineering executive who has built and led some of the strongest teams in the software industry. He studied computer science and math at MIT and has a PhD in computer science from CMU. He was a founding employee and chief scientist of Endeca, a search pioneer that Oracle acquired for $1.1B. He led a local search team at Google. He was a director of data science and engineering at LinkedIn, and he established their query understanding team. Daniel is a widely recognized writer and speaker. He is frequently invited to speak at academic and industry conferences, particularly in the areas of information retrieval, web science, and data science. He has written the definitive textbook on faceted search (now a standard for ecommerce sites), established an annual symposium on human-computer interaction and information retrieval, and authored 24 US patents. His social media posts have attracted over a million page views. Daniel advises and consults for companies that can benefit strategically from his expertise. His clients range from early-stage startups to "unicorn" technology companies like Etsy and Pinterest. He helps companies make decisions around algorithms, technology, product strategy, hiring, and organizational structure.
Intro to Data Science for Enterprise Big Data
If you need a different format (PDF, PPT) instead of Keynote, please email me: pnathan AT concurrentinc DOT com
An overview of Data Science for Enterprise Big Data. In other words, how to combine structured and unstructured data, leveraging the tools of automation and mathematics, for highly scalable businesses. We discuss management strategy for building Data Science teams, basic requirements of the "science" in Data Science, and typical data access patterns for working with Big Data. We review some great algorithms, tools, and truisms for building a Data Science practice, and provide plus some great references to read for further study.
Presented initially at the Enterprise Big Data meetup at Tata Consultancy Services, Santa Clara, 2012-08-20 http://www.meetup.com/Enterprise-Big-Data/events/77635202/
Be Data Informed Without Being a Data Scientist
You are a designer, or a coder, or a manager. Maybe you are even a unicorn. But you are not a data scientist. Still, you want to get more out of the mountain of data you have about your site or app to create a better user experience. No problem. Learn a process of data thinking that will help you to analyze, visualize, and really use data about your website or app without all the bothersome math and python programming.
Data Acquisition Checklist 101
Data acquisition is the biggest hurdle in most big data projects. Here is a detailed checklist that can be used to make sure that you’re all set to acquire data for your business.
Design like a Human in the Age of Algorithms
Algorithms are shaping our experience every day. Our Facebook feeds, our Spotify playlists, our Amazon recommendations are creating a personalized window into a world driven by algorithms. As design becomes less about a screen and more about augmenting humans with extended capabilities, new ideas, even potentially more emotional awareness, we will need algorithms. But humans are complicated. Humans change all the time. Algorithms have a hard time with that. Design thinking can bridge the gap between machine learning and human intelligence.
How to Become a Data Scientist
How to Become a Data Scientist
SF Data Science Meetup, June 30, 2014
Video of this talk is available here: https://www.youtube.com/watch?v=c52IOlnPw08
More information at: http://www.zipfianacademy.com
Zipfian Academy @ Crowdflower
4 Reasons to Choose Web Scraping for your Travel Portal
Acquiring fresh and high quality data at the right time is one of the most important tasks for any business. Especially if you are managing a travel portal, you need latest hotel reviews, pricing, flight details and other related information to power your website. Here is why you should use web scraping for acquiring data for your travel portal.
Finding Our Happy Place in the Internet of Things
In the future, we will all be better people. And our technology will be better too. Or will it? With connected devices becoming a canvas for our lives, we need new principles and practices to design with greater humanity.
Bridging the Gap Between Data Science & Engineer: Building High-Performance T...
Data scientists, data engineers, and data businesspeople are critical to leveraging data in any organization. A common complaint from data science managers is that data scientists invest time prototyping algorithms, and throw them over a proverbial fence to engineers to implement, only to find the algorithms must be rebuilt from scratch to scale. This is a symptom of a broader ailment -- that data teams are often designed as functional silos without proper communication and planning.
This talk outlines a framework to build and organize a data team that produces better results, minimizes wasted effort among team members, and ships great data products.
Generation Z and the Future of Technology
GenZ is the largest generation yet and they are truly digital natives. The attitudes and behaviors of Zs will have a huge impact on the future of technology. Grounded in data from hundreds of online research sessions, diaries, and interviews, learn what Gen Z really does online and the ways it will change how we design the experience.
Big Data [sorry] & Data Science: What Does a Data Scientist Do?
What 'kind of things' does a data scientist do? What are the foundations and principles of data science? What is a Data Product? What does the data science process looks like? Learning from data: Data Modeling or Algorithmic Modeling? - talk by Carlos Somohano @ds_ldn at The Cloud and Big Data: HDInsight on Azure London 25/01/13
Big Data’s Potential for the Real Estate Industry: 2021
Many real estate firms have long made decisions based on a combination of intuition and traditional, retrospective data. Today, a host of new variables make it possible to paint more vivid pictures of a location’s future risks and opportunities.
In this quickly technologizing industry, arming your team with the most robust data available and making important decisions based on the data is going to determine who wins and loses.Big data will become the key basis of competition and growth for individual firms, enhancing productivity and creating significant value for the world economy. In this white paper, we explore the real estate outlook for financial investment in 2021 and use cases demonstrating the power of data in transforming the real estate industry.
Octoparse competitors.pdf
Looking for a similar tool like Octoparse? We have conducted thorough research on tools that can process web data to draw actionable insights. The results were amazing, as most of the web scraping tools that are available in the market offer unique value propositions for unique data requirements, differing from business to business. As you read further, you will be able to figure out the best Octoparse competitors & alternatives for your organizational data needs.
Most of the users use Octoparse to figure out how the market is functioning and to conduct data verification. However, conducting broad-level research might not always work for companies running in a niche domain. There are a lot of tools available today, offering value services like: easy usage, value for money, better user rating, getting structured data and etc, that could be a great fit for your business requirements. But first, let’s understand how Octoparse web scraping works.
Parsehub and competitior ppt.pptx
How to Choose the Right Competitors & Alternatives of ParseHub Web Scraping Software?
Web scraping is generally used to understand the marketplaces and get visibility on the pricing structure of your competitors in the niche your company is invested in. Getting a fair understanding of various web scraping products and Parsehub competitors and alternatives will enable you to make informed decisions to grow your business. Read more to know how these tools work, scaling, delivery, target customers, and shortcomings. Read further, to take a look at companies offering data services according to industries, user rating, accessibility, deliverables, speed, interface, customer service, and technical challenges. But before we dive into this, let’s understand what web scraping is and how to access the ParseHub Web Scraping Software.
Product Visibility- What Is Seen First, Will ppt.pptx
Putting your products on multiple eCommerce websites may give you a broad reach, but might not be enough for them to be “visible”. Creating quality blogs or short videos on several themes could help you find a wider reach!You can partake in multiple activities like –
Talk about the USP of your products or highlight the star products.
Share a comparison of your products with your competitors.
Discuss topics related to the your product and services delivered by you. When users go to a product page, right after the images, they look at the heading and the description. Let’s take an example of a product listed on Amazon, to figure out how both headings and descriptions can increase the sales of your products.Read the complaints they have with similar products. Decide upon the size and quantity options that would suit the user base most. Understand the price point that is desired. And lo and behold you would have increased your product visibility!
Data Trends in Fashion Industry
Data plays a vital role in the fashion industry. It is used to drive decisions and strategy that generate sales, gain a better understanding of customers, and boost overall profit. Fashion designers and companies use data on a daily basis run a successful fashion business. However, the commonly perceived data used by fashion designers differ from the standard mathematical statistics commonly associated with the term “data”. Hence, data is not usually associated with the word fashion.
But, today’s top fashion houses are deploying several ways to use emerging analytical technologies in fashion retail today. We explore how the modern fashion industry uses data.
More Related Content
Viewers also liked
Myths and Mathemagical Superpowers of Data Scientists
Some people think data scientists are mythical beings, like unicorns, or they are some sort of nouveau fad that will quickly fade. Not true, says IBM big data evangelist James Kobielus. In this engaging presentation, with artwork created by Angela Tuminello, Kobielus debunks 10 myths about data scientists and their role in analytics and big data. You might also want to read the full blog by Kobielus that spawned this presentation: "Data Scientists: Myths and Mathemagical Superpowers" - http://ibm.co/PqF7Jn
For more information, visit http://www.ibmbigdatahub.com
Introduction to R for Data Mining
We at Revolution Analytics are often asked “What is the best way to learn R?” While acknowledging that there may be as many effective learning styles as there are people we have identified three factors that greatly facilitate learning R. For a quick start:
- Find a way of orienting yourself in the open source R world
- Have a definite application area in mind
- Set an initial goal of doing something useful and then build on it
In this webinar, we focus on data mining as the application area and show how anyone with just a basic knowledge of elementary data mining techniques can become immediately productive in R. We will:
- Provide an orientation to R’s data mining resources
- Show how to use the "point and click" open source data mining GUI, rattle, to perform the basic data mining functions of exploring and visualizing data, building classification models on training data sets, and using these models to classify new data.
- Show the simple R commands to accomplish these same tasks without the GUI
- Demonstrate how to build on these fundamental skills to gain further competence in R
- Move away from using small test data sets and show with the same level of skill one could analyze some fairly large data sets with RevoScaleR
Data scientists and analysts using other statistical software as well as students who are new to data mining should come away with a plan for getting started with R.
How to Interview a Data Scientist
How To Interview a Data Scientist
Daniel Tunkelang
Presented at the O'Reilly Strata 2013 Conference
Video: https://www.youtube.com/watch?v=gUTuESHKbXI
Interviewing data scientists is hard. The tech press sporadically publishes “best” interview questions that are cringe-worthy.
At LinkedIn, we put a heavy emphasis on the ability to think through the problems we work on. For example, if someone claims expertise in machine learning, we ask them to apply it to one of our recommendation problems. And, when we test coding and algorithmic problem solving, we do it with real problems that we’ve faced in the course of our day jobs. In general, we try as hard as possible to make the interview process representative of actual work.
In this session, I’ll offer general principles and concrete examples of how to interview data scientists. I’ll also touch on the challenges of sourcing and closing top candidates.
A Statistician's View on Big Data and Data Science (Version 1)
Presentation given by Dr. Diego Kuonen, CStat PStat CSci, on November 20, 2013, at the "IBM Developer Days 2013" in Zurich, Switzerland.
ABSTRACT
There is no question that big data has hit the business, government and scientific sectors. The demand for skills in data science is unprecedented in sectors where value, competitiveness and efficiency are driven by data. However, there is plenty of misleading hype around the terms big data and data science. This presentation gives a professional statistician's view on these terms and illustrates the connection between data science and statistics.
The presentation is also available at http://www.statoo.com/BigDataDataScience/.
Enterprise Intelligence
Enterprise Intelligence: Putting the Pieces Together
http://enterpriserelevance.com/kdd2016/keynote.html
These slides are for a keynote presentation delivered at the Workshop on Enterprise Intelligence, held in conjunction with the 22nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2016).
About the author:
Daniel Tunkelang is a data science and engineering executive who has built and led some of the strongest teams in the software industry. He studied computer science and math at MIT and has a PhD in computer science from CMU. He was a founding employee and chief scientist of Endeca, a search pioneer that Oracle acquired for $1.1B. He led a local search team at Google. He was a director of data science and engineering at LinkedIn, and he established their query understanding team. Daniel is a widely recognized writer and speaker. He is frequently invited to speak at academic and industry conferences, particularly in the areas of information retrieval, web science, and data science. He has written the definitive textbook on faceted search (now a standard for ecommerce sites), established an annual symposium on human-computer interaction and information retrieval, and authored 24 US patents. His social media posts have attracted over a million page views. Daniel advises and consults for companies that can benefit strategically from his expertise. His clients range from early-stage startups to "unicorn" technology companies like Etsy and Pinterest. He helps companies make decisions around algorithms, technology, product strategy, hiring, and organizational structure.
Intro to Data Science for Enterprise Big Data
If you need a different format (PDF, PPT) instead of Keynote, please email me: pnathan AT concurrentinc DOT com
An overview of Data Science for Enterprise Big Data. In other words, how to combine structured and unstructured data, leveraging the tools of automation and mathematics, for highly scalable businesses. We discuss management strategy for building Data Science teams, basic requirements of the "science" in Data Science, and typical data access patterns for working with Big Data. We review some great algorithms, tools, and truisms for building a Data Science practice, and provide plus some great references to read for further study.
Presented initially at the Enterprise Big Data meetup at Tata Consultancy Services, Santa Clara, 2012-08-20 http://www.meetup.com/Enterprise-Big-Data/events/77635202/
Be Data Informed Without Being a Data Scientist
You are a designer, or a coder, or a manager. Maybe you are even a unicorn. But you are not a data scientist. Still, you want to get more out of the mountain of data you have about your site or app to create a better user experience. No problem. Learn a process of data thinking that will help you to analyze, visualize, and really use data about your website or app without all the bothersome math and python programming.
Data Acquisition Checklist 101
Data acquisition is the biggest hurdle in most big data projects. Here is a detailed checklist that can be used to make sure that you’re all set to acquire data for your business.
Design like a Human in the Age of Algorithms
Algorithms are shaping our experience every day. Our Facebook feeds, our Spotify playlists, our Amazon recommendations are creating a personalized window into a world driven by algorithms. As design becomes less about a screen and more about augmenting humans with extended capabilities, new ideas, even potentially more emotional awareness, we will need algorithms. But humans are complicated. Humans change all the time. Algorithms have a hard time with that. Design thinking can bridge the gap between machine learning and human intelligence.
How to Become a Data Scientist
How to Become a Data Scientist
SF Data Science Meetup, June 30, 2014
Video of this talk is available here: https://www.youtube.com/watch?v=c52IOlnPw08
More information at: http://www.zipfianacademy.com
Zipfian Academy @ Crowdflower
4 Reasons to Choose Web Scraping for your Travel Portal
Acquiring fresh and high quality data at the right time is one of the most important tasks for any business. Especially if you are managing a travel portal, you need latest hotel reviews, pricing, flight details and other related information to power your website. Here is why you should use web scraping for acquiring data for your travel portal.
Finding Our Happy Place in the Internet of Things
In the future, we will all be better people. And our technology will be better too. Or will it? With connected devices becoming a canvas for our lives, we need new principles and practices to design with greater humanity.
Bridging the Gap Between Data Science & Engineer: Building High-Performance T...
Data scientists, data engineers, and data businesspeople are critical to leveraging data in any organization. A common complaint from data science managers is that data scientists invest time prototyping algorithms, and throw them over a proverbial fence to engineers to implement, only to find the algorithms must be rebuilt from scratch to scale. This is a symptom of a broader ailment -- that data teams are often designed as functional silos without proper communication and planning.
This talk outlines a framework to build and organize a data team that produces better results, minimizes wasted effort among team members, and ships great data products.
Generation Z and the Future of Technology
GenZ is the largest generation yet and they are truly digital natives. The attitudes and behaviors of Zs will have a huge impact on the future of technology. Grounded in data from hundreds of online research sessions, diaries, and interviews, learn what Gen Z really does online and the ways it will change how we design the experience.
Big Data [sorry] & Data Science: What Does a Data Scientist Do?
What 'kind of things' does a data scientist do? What are the foundations and principles of data science? What is a Data Product? What does the data science process looks like? Learning from data: Data Modeling or Algorithmic Modeling? - talk by Carlos Somohano @ds_ldn at The Cloud and Big Data: HDInsight on Azure London 25/01/13
Viewers also liked (15)
Myths and Mathemagical Superpowers of Data Scientists
Myths and Mathemagical Superpowers of Data Scientists
A Statistician's View on Big Data and Data Science (Version 1)
A Statistician's View on Big Data and Data Science (Version 1)
4 Reasons to Choose Web Scraping for your Travel Portal
4 Reasons to Choose Web Scraping for your Travel Portal
Bridging the Gap Between Data Science & Engineer: Building High-Performance T...
Bridging the Gap Between Data Science & Engineer: Building High-Performance T...
Big Data [sorry] & Data Science: What Does a Data Scientist Do?
Big Data [sorry] & Data Science: What Does a Data Scientist Do?
More from PromptCloud
Big Data’s Potential for the Real Estate Industry: 2021
Many real estate firms have long made decisions based on a combination of intuition and traditional, retrospective data. Today, a host of new variables make it possible to paint more vivid pictures of a location’s future risks and opportunities.
In this quickly technologizing industry, arming your team with the most robust data available and making important decisions based on the data is going to determine who wins and loses.Big data will become the key basis of competition and growth for individual firms, enhancing productivity and creating significant value for the world economy. In this white paper, we explore the real estate outlook for financial investment in 2021 and use cases demonstrating the power of data in transforming the real estate industry.
Octoparse competitors.pdf
Looking for a similar tool like Octoparse? We have conducted thorough research on tools that can process web data to draw actionable insights. The results were amazing, as most of the web scraping tools that are available in the market offer unique value propositions for unique data requirements, differing from business to business. As you read further, you will be able to figure out the best Octoparse competitors & alternatives for your organizational data needs.
Most of the users use Octoparse to figure out how the market is functioning and to conduct data verification. However, conducting broad-level research might not always work for companies running in a niche domain. There are a lot of tools available today, offering value services like: easy usage, value for money, better user rating, getting structured data and etc, that could be a great fit for your business requirements. But first, let’s understand how Octoparse web scraping works.
Parsehub and competitior ppt.pptx
How to Choose the Right Competitors & Alternatives of ParseHub Web Scraping Software?
Web scraping is generally used to understand the marketplaces and get visibility on the pricing structure of your competitors in the niche your company is invested in. Getting a fair understanding of various web scraping products and Parsehub competitors and alternatives will enable you to make informed decisions to grow your business. Read more to know how these tools work, scaling, delivery, target customers, and shortcomings. Read further, to take a look at companies offering data services according to industries, user rating, accessibility, deliverables, speed, interface, customer service, and technical challenges. But before we dive into this, let’s understand what web scraping is and how to access the ParseHub Web Scraping Software.
Product Visibility- What Is Seen First, Will ppt.pptx
Putting your products on multiple eCommerce websites may give you a broad reach, but might not be enough for them to be “visible”. Creating quality blogs or short videos on several themes could help you find a wider reach!You can partake in multiple activities like –
Talk about the USP of your products or highlight the star products.
Share a comparison of your products with your competitors.
Discuss topics related to the your product and services delivered by you. When users go to a product page, right after the images, they look at the heading and the description. Let’s take an example of a product listed on Amazon, to figure out how both headings and descriptions can increase the sales of your products.Read the complaints they have with similar products. Decide upon the size and quantity options that would suit the user base most. Understand the price point that is desired. And lo and behold you would have increased your product visibility!
Data Trends in Fashion Industry
Data plays a vital role in the fashion industry. It is used to drive decisions and strategy that generate sales, gain a better understanding of customers, and boost overall profit. Fashion designers and companies use data on a daily basis run a successful fashion business. However, the commonly perceived data used by fashion designers differ from the standard mathematical statistics commonly associated with the term “data”. Hence, data is not usually associated with the word fashion.
But, today’s top fashion houses are deploying several ways to use emerging analytical technologies in fashion retail today. We explore how the modern fashion industry uses data.
Data Standardization with Web Data Integration
Before analyzing data aggregated from multiple sources, it is essential to first standardize the datasets. At PromptCloud, we put special emphasis on this process and understand that as a web crawling company, our solution must enable our clients to integrate data efficiently.
Visualizing Marvel Cinematic Universe Movies
Check out an interesting infographic, uncovering facts of Marvel Cinematic Universe movies: Data from IMDB
15 Key Metrics Every E-commerce Business Should Track
Take a look at these e-commerce metrics that you should capture for a profitable e-commerce business.
Top Amazon Services for Ecommerce Players
This presentation lists the top services offered by Amazon for ecommerce players -- from AWS and FBA to advertising and Amazon Pay.
The Birth of a Web Crawling Bot
Here are the various stages involved in the creation of a web crawling bot.
Upcoming Applications of Artificial intelligence in 2019
From AI Chips to healthcare and surveillance, here are some of the applications of Artificial Intelligence that we can witness in the year 2019.
Zipcode based price benchmarking for retailers
Here's our case study of a popular e-commerce platform based out of the United States, seeking data to be extracted from the web to enhance its pricing and product strategy.
Analyzing Positiveness in 160+ Holiday Songs
It is known that during any kind of celebration music is indispensable and the holiday season is no different. Since this time of the year brings positiveness, we decided to analyze the holiday songs to uncover some interesting insights related to musical features and positiveness in songs.
PromptCloud's Year in Review - 2019
What a year 2018 has been for the data ecosystem! We believe the high-magnitude and rapid demand for alt-data (especially web data) from companies of various sizes across industries is a remarkable element of this year.
For PromptCloud, it has always been about moving the needle when it comes to democratization of web data access. We’re fortunate enough to have built a team that absolutely loves the ease of information flow offered by the internet and wants to share the same with the businesses across the globe.
We’re on a journey to make a dent in the alt-data space with laser-focused teams that are paranoid about the data quality delivered to our customers. In honor of our successful clients and their incredible growth powered by our talented data wizards, let’s spare a moment to celebrate PromptCloud’s year in review.
Top Data Analytics Trends for 2019
This presentation will discuss the industry sectors and trends that will witness major growth in applications of big data analytics.
10 Mobile App Ideas that can be Fueled by Web Scraping
We discuss various applications of web crawling and alternate data to fuel 10 potential mobile apps. The ideas range from reverse image search engine powered AI to voice of customer in ecommerce domain.
How Web Scraping Can Help Affiliate Marketers
This presentation discusses how web scraping services can be deployed to acquire trending ecommerce product data for better conversion in affiliate marketing.
Hotel Review Data Analysis
In this study, we analyze the reviews for the top 10 most expensive and least expensive hotels based out of London to compare various aspects of the rating and review text.
More from PromptCloud (20)
Big Data’s Potential for the Real Estate Industry: 2021
Big Data’s Potential for the Real Estate Industry: 2021
Product Visibility- What Is Seen First, Will ppt.pptx
Product Visibility- What Is Seen First, Will ppt.pptx
15 Key Metrics Every E-commerce Business Should Track
15 Key Metrics Every E-commerce Business Should Track
Upcoming Applications of Artificial intelligence in 2019
Upcoming Applications of Artificial intelligence in 2019
10 Mobile App Ideas that can be Fueled by Web Scraping
10 Mobile App Ideas that can be Fueled by Web Scraping
Recently uploaded
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
Reflecting on new architectures for knowledge based systems in light of generative ai
Bits & Pixels using AI for Good.........
A whirlwind tour of tech & AI for socio-environmental impact.
Knowledge engineering: from people to machines and back
Keynote at the 21st European Semantic Web Conference
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
“AGI should be open source and in the public domain at the service of humanity and the planet.”
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP of Product, Amplitude
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scalable Platform by VP of Product, The New York Times
UiPath Test Automation using UiPath Test Suite series, part 4
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Essentials of Automations: Optimizing FME Workflows with Parameters
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Designing Great Products: The Power of Design and Leadership by Chief Designe...
Designing Great Products: The Power of Design and Leadership by Chief Designer, Beats by Dr Dre
Connector Corner: Automate dynamic content and events by pushing a button
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
JMeter webinar - integration with InfluxDB and Grafana
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Accelerate your Kubernetes clusters with Varnish Caching
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, Product School
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of Product, Slack
Recently uploaded (20)
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
To Graph or Not to Graph Knowledge Graph Architectures and LLMs
Knowledge engineering: from people to machines and back
Knowledge engineering: from people to machines and back
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
GenAISummit 2024 May 28 Sri Ambati Keynote: AGI Belongs to The Community in O...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Daily Decisions to Bottom Line: Connecting Product Work to Revenue by VP...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
From Siloed Products to Connected Ecosystem: Building a Sustainable and Scala...
UiPath Test Automation using UiPath Test Suite series, part 4
UiPath Test Automation using UiPath Test Suite series, part 4
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Essentials of Automations: Optimizing FME Workflows with Parameters
Essentials of Automations: Optimizing FME Workflows with Parameters
Designing Great Products: The Power of Design and Leadership by Chief Designe...
Designing Great Products: The Power of Design and Leadership by Chief Designe...
Connector Corner: Automate dynamic content and events by pushing a button
Connector Corner: Automate dynamic content and events by pushing a button
JMeter webinar - integration with InfluxDB and Grafana
JMeter webinar - integration with InfluxDB and Grafana
Accelerate your Kubernetes clusters with Varnish Caching
Accelerate your Kubernetes clusters with Varnish Caching
How world-class product teams are winning in the AI era by CEO and Founder, P...
How world-class product teams are winning in the AI era by CEO and Founder, P...
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
State of ICS and IoT Cyber Threat Landscape Report 2024 preview
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
AI for Every Business: Unlocking Your Product's Universal Potential by VP of ...
Monitoring Java Application Security with JDK Tools and JFR Events
Monitoring Java Application Security with JDK Tools and JFR Events