"Trying to understand mathematically how the human mind works using big data."
"We're living in the age of big data, where we have more access to data than ever before."
"With big data, we get a telescope to look at different chunks and record how many galaxies there are in each chunk of the sky."
"All big data comes from the same place: the past."
"I think big data is going to answer a lot of these questions."
"The reason we can do it so quickly is because we have big data."
"By integrating big data and thick data, they not only improved their business, but they transformed how we consume media."
"We're forecasting 125 million live vehicles on platform. We have visibility of more than 60% of where that's coming from already."
"Palantir is a big player in the big data industry which is fast growing and will likely see big changes in 2021 and beyond."
"Kafka handles large amounts of data; we produced 10 million events and it handled them with no trouble."
"Teledoc and Livongo are both data science organizations that are coming together and using big data to provide a total healthcare ecosystem."
"We have terabytes of data being collected every week."
"We live in an age of mass surveillance and big data."
"It's incredibly accurate, predicting disease outbreaks and events like civil unrest."
"Amazon Athena is a serverless option to perform analysis with giant queries."
"Big data and crowd wisdom have become central to how many companies approach business."
"With these big data sets and careful statistical methods, they have shown remarkable ability to forecast a lot of interesting things."
"Scaling up models on larger datasets will go surprisingly far."
"Imagine you had a big data OS, it's like the OS of the future for building all the software your organization needs."
"Walmart stores information about all the products it sells, generating a tremendous amount of data."
"AI which is maybe another word for one Enriquez big data really getting intelligence out of all the information is out there in the world is getting some real traction."
"Using Google Cloud's bigquery, business analysts of Ferrero were able to store and analyze massive data sets in a very reliable fast and affordable manner."
"Capability to process billions of rows in seconds."
"DataProc is a managed service which allows you to run Spark or Hadoop jobs, especially if you're interested in big data workload."
"BigQuery is a fully managed serverless data warehouse that enables scalable analysis over petabytes of data."
"With the era of big data, topics like artificial intelligence and machine learning are also going to be very important when combined with GIS and domain knowledge."
"The big data can end up that some government of a foreign country can know more about you as a nation state."
"There is a bit of a bandwagon right now with machine learning and big data, but one of the key sort of deeper issues that isn't resolved yet… is really helping disentangle causation and correlation."
"We're not talking about humans being out of the loop, but I think we ought to be talking about how crappy human judgment could be made better by analysis of big data."
"AI and big data do not yet have all the answers."
"The threat from big data analysis used by governments and authoritarian regimes is terrifying"
"Google's data warehouse is bigquery, you know hopefully people have heard of it by now and it's our enterprise data warehouse for analytics."
"Spark is particularly valuable for data engineers, data scientists, and big data professionals who deal with large-scale data processing."
"Spark: a replacement for Hadoop MapReduce, designed to work in memory as much as possible, performing up to 100 times faster than MapReduce."
"Harnessing big data to develop a scientific evidence base for economic and social policy can be extremely powerful."
"Smart analytics tap into big data and business intelligence Cloud offerings."
"The rapid growth in the science of complex networks and modeling big data has made graph theory a popular technique."
"Learning a big data framework is a fantastic way to stand out from the crowd."
"Every actor in my organization can be productive in a big data stack."
"Non-technical people need to be able to make decisions with [big data], and they're the only company of my knowledge that has figured that out."
"Apache spark is a unified analytics engine for big data processing with built in modules for streaming, sequel, machine learning, and graph processing."
"Big Data engineers can earn up to $121,000 to $251,000 per annum."
"Multi-scale physics is one of the grand challenge problems of this big data era."
"Koopman analysis fits very nicely in the context of data science with increasing amounts of data."
"Cloud technology provides scalable and distributed computing resources that can handle big data processing and storage requirements."
"He's using big data to understand how to give kids from disadvantaged backgrounds better chances of succeeding."
"Data is becoming more distributed, data types are changing, setting up and maintaining a big data infrastructure is very complex."
"Big data is the new norm when it comes to data."
"As we'll discuss further, big data is the new norm when it comes to data."
"Big data is nearly impossible to process using traditional methods because there is so much of it."
"Big data refers to data that is nearly impossible to process using traditional methods because there is so much of it."
"Python has become the ubiquitous language across many different domains and big data."
"Big Data approaches are actually replacing the standard approach of the sciences."
"Companies like Airbnb, Netflix, and Uber were using AI for massive amounts of data processing."
"We live in a world of information now, and there's a difference between accessing big data and experiencing it."
"If you have a million people hooked up with biomonitors, you're going to learn within a matter of months what works and what doesn't."
"EMR stands for Elastic Map Reduce, which is an AWS service that allows you to scale and run your big data server on demand on the cloud."
"When you spin up your EMR cluster, you can choose whatever big data framework that you need."
"Big data refers to a large and vast variety or scope of data points that is being gathered and collected at extremely fast rates."
"ArcGIS is now IoT and big data ready, so you can tap into all of that real-time information, all of that big data, you can store it and manage it in ArcGIS."
"Big data is really kind of a buzzword... it's big when the size of the data or the speed at which it's acquired challenges your current methodological toolbox."
"Spark is a unified processing engine that allows you to build all sorts of cool big data applications."
"No big data approach and no modern approach to data science can be successful without an understanding of causal effects."
"The amount of data that would be required for this is absolutely staggering."
"Machine learning allows us to analyze complex big data."
"If you can get that magic combination of networking benefits pushing your cost down and the fact that you can sell more to your customers with big data, you've got the magic combination to becoming a valuable company."
"We're entering an era of big data in biomedicine."
"If you are an organization that has a hang of a lot of data, then you end up being able to afford some crazy cool complex models because you have enough data to handle it."
"The program is designed to highlight the role of large omics data sets or big data that is shaping modern biomedical innovation."
"MongoDB is really a good choice for things like storing big documents of information or text."
"Big data is just generally considered to be sets of data that really go beyond the range of a typical relational database to store."
"I love applying math and machine learning to Big Data to better make sense of the world."
"It's becoming the market leader in big data processing frameworks."
"I use Hive every day on my job, it's still a market leader, it's still a great way to interact with big data."
"Trillions of data points are processed every day."
"You're working with billions of rows of data."
"The hottest Big Data platform out there is SPARC."
"It's incredibly fast. You can get answers to queries literally in milliseconds on data sets that contain billions or trillions of rows."
"Spark enables applications in Hadoop clusters to run up to 100 times faster in memory, and 10 times faster even when running on disk."
"The term big data refers to the rapidly expanding amount of data that is being stored and used by organizations."
"Big data involves data with volume, diversity, and complexity that requires new techniques, algorithms, and analysis to extract valuable knowledge."
"The ability to deal with faults is one of the key aspects we want to keep in mind when designing distributed solutions for big data."
"Spark is a distributed analytics engine for big data, so it's a technology that helps you run code in a distributed fashion on many machines at the same time."
"If you need to produce and consume data at a high volume and velocity, NoSQL might be for you."
"We have more data and we need more powerful tools to fully utilize all this information to get us a good prediction."
"We are getting more and more data so we really need to build scalable solutions."
"The tool operates fast on big data, which makes its performance powerful."
"Deep learning is a highly optimized way of doing a lot of stuff where we have really big datasets and you need to do stuff faster in a more robust fashion."
"There's huge amounts of data that are being contributed and collated in these central databases."
"The computational technology in medicine does generally involve a lot of large data kind of techniques."
"A data lake is a centralized, secure repository that enables you to govern, discover, share, and analyze structured and unstructured data at any scale."
"Delta Lake offers ACID transactions on Spark, upserts and deletes, scalable metadata handling, schema enforcement, time travel, and unified streaming and batch data processing."
"We're trying to create a big data scalable platform that can do your entire ML pipeline."
"There are 200,000 plus companies worldwide using this platform to do their big data and machine learning."
"We can usually see performance in under a second for multi-billion row queries."
"Big data is opening up some opportunities in organizational behavior."
"Big data is data that doesn't fit on screen."
"When it comes to big data, you want to have that commodity scaling. Vertical scaling has a certain threshold, but with horizontal scaling, you can add as many nodes as you like based on your storage requirement."
"Looks like big data is the future, of course it is, and Snowflake's well positioned to capture big market share."
"Analyze big data and make data-driven predictions through probabilistic modeling and statistical inference."
"NoSQL is used for big data and real-time web applications."
"When you build big data systems, build decoupled data pipelines and use the right tool for the job."
"We've tried to make accessing big data for you really very much like accessing the data that you would otherwise access."
"Apache Spark is one of the best frameworks to handle large data and perform analysis."
"Hadoop is a solution which companies would want to use if they would want to process big data."
"But he introduced us to the possibility of using these kinds of resources for doing machine learning, and this is sort of maybe the future of looking at big data, and getting useful insights."
"We are now in the era of big data in biology."
"As big data came into place, we not only had data in volume and velocity, but we also had variety of data."
"Hadoop is meant to tackle problems large in scale."
"We are a Pioneer in big data and AI Technologies."
"Big data refers to massive datasets that are produced by people through their interactions with some of the newer technologies."
"Big data is usually referenced by three V's: volume, velocity, and variety."
"Bringing compute to data is absolutely the path forward for Big Data."
"We are living in the big data era."
"Big data doesn't have to be big costs if you architect it correctly."
"Big data analytics assists business organizations to take decisions depending on the analysis performed."
"The purpose of this multi-machine parallel processing is to allow you to process large volumes of data and perform very complex resource intense processing on big data quickly."
"Azure Databricks is a big data cluster that runs on Apache Spark where we can easily set up our spark cluster without any need of our hardware and we can run our code to analyze and visualize in big data."
"We actually successfully took over the Big Data world."
"Apache Spark is an open-source project for large-scale distributed computations."
"Strong SQL and big data experience is essential."
"We've fundamentally changed the physics of big data."
"The future of big data is compute data convergence."
"Why can't we take the UNIX philosophy to Big Data?"
"Hadoop is a framework that manages big data storage in a distributed way and processes it parallelly."
"It's well-suited for storing unstructured data like multimedia, video files, photos, and other big data."
"Scaling out is really the only technique that works when you get to really big things."
"You are able to plot, clean, and analyze large data sets and so much more."
"Big data is when you have like 50 terabytes or 100 terabytes or 150 terabytes of data."
"Big Data technology helps to manage and process huge amounts of data in a cost-efficient manner."
"Big Data technology understands and navigates Big Data sources, manages and stores a huge volume of a variety of data, processes data in reasonable time, ingests data at a high speed, analyzes unstructured data, and is fault-tolerant."
"MapReduce is a programming model and an associated implementation for processing and generating large data sets with parallel and distributed algorithms on a cluster."
"Big Data is typically characterized by three V's: volume, velocity, and variety."
"Real-time Big Data refers to handling a massive amount of business data as soon as the data is created."
"Hadoop is a framework that allows for distributed processing of large data sets across clusters of commodity computers using simple programming models."
"Organizations are interested in gaining insights or finding the hidden treasure in the so-called big data."
"Big data brings its own challenges; huge amount of data is getting generated every day."
"Neural networks are useful and powerful in the case of large datasets with many variables."
"Spark provides performance which is 10 times faster than MapReduce on the disk and 100 times faster on network or memory."
"If you have a good skill on Spark, there is definitely a very valuable skill right now in the market in terms of big data processing."
"Machine learning today is training novel architectures on big data, and Tesla needs the biggest data to solve the biggest problem that of real-world autonomous driving."
"Learning through big data experiences and exploration."
"It's important because nowadays we're doing MapReduce, we're doing Elixir, we're crunching through this ton of data that we have on user behaviors and things like that."
"Event Hub is perfect for big data pipelines."
"The real promise of big data is it's changing the whole way humans will solve problems."
"Main thing you need to remember is it is an open-source programming framework for distributed processing and distributed storage for large datasets."
"The typical aspect of big data is not about data itself; it is the ability to discover useful information hidden in data."
"If you have a large data set, either structured or unstructured, and want to process in a distributed manner without spending time on provisioning data clusters, the best service available is Azure Data Lake Analytics."
"I would like to thank you for your attention and I hope to see you on the forums and in other places talking U-SQL and exchanging our experiences on processing big data."
"The size of the data sets that we're thinking now in terms of terabytes and petabytes."
"Big data has a bit of hype behind it for sure, but at the core is this idea that we've got commodity hardware at your fingertips."
"The challenges with big data are mainly engineering problems."
"We see the technology as complementary and we think that over time more and more big data architectures will include storm for real-time processing of data."