All Things Distributed

JANUARY 20, 2020

Back when Jeff Bezos filled orders in his garage and drove packages to the post office himself, crunching the numbers on costs, tracking inventory, and forecasting future demand was relatively simple.

Big Data 196

Big Data Logistics Retail Government 196

Uber Engineering

OCTOBER 17, 2018

To accomplish this, Uber relies heavily on making data-driven decisions at every level, from forecasting rider demand during high traffic events to identifying and addressing bottlenecks … The post Uber’s Big Data Platform: 100+ Petabytes with Minute Latency appeared first on Uber Engineering Blog.

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Big Data Latency Transportation Traffic 109

Uber Engineering

AUGUST 3, 2018

From driver and rider locations and destinations, to restaurant orders and payment transactions, every interaction on Uber’s transportation platform is driven by data.

Big Data 110

Big Data Transportation Engineering Storage 110

All Things Distributed

AUGUST 18, 2011

Driving down the cost of Big-Data analytics. The Amazon Elastic MapReduce (EMR) team announced today the ability to seamlessly use Amazon EC2 Spot Instances with their service, significantly driving down the cost of data analytics in the cloud. Driving down the cost of Big-Data analytics. Comments ().

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Big Data Analytics AWS Cloud 94

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. Key challenges. Performance.

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Big Data Storage Benchmarking Hardware 63

Uber Engineering

MARCH 21, 2024

Discover real-time query analytics and governance with DataCentral: Uber’s big data observability powerhouse, tackling millions of queries in petabyte-scale environments.

Big Data 68

Big Data Government Analytics 68

DZone

FEBRUARY 23, 2023

Introduction With big data streaming platform and event ingestion service Azure Event Hubs , millions of events can be received and processed in a single second. Any real-time analytics provider or batching/storage adaptor can transform and store data supplied to an event hub.

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Azure Big Data Storage Analytics 306

DZone

JUNE 3, 2024

This is especially the case when it comes to taking advantage of vast amounts of data stored in cloud platforms like Amazon S3 - Simple Storage Service, which has become a central repository of data types ranging from the content of web applications to big data analytics.

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Big Data AWS Storage Analytics 278

Rigor

MAY 22, 2019

Big data is like the pollution of the information age. The Big Data Struggle and Performance Reporting. As the big data era brings in multiple options for visualization, it has become apparent that not all solutions are created equal. Conclusion.

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Big Data Monitoring Performance Metrics 76

The Morning Paper

DECEMBER 13, 2020

An overview of end-to-end entity resolution for big data , Christophides et al., It’s an important part of many modern data workflows, and an area I’ve been wrestling with in one of my own projects. ACM Computing Surveys, Dec. 2020, Article No.

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Big Data Open Source Processing Analytics 83

High Scalability

SEPTEMBER 14, 2020

This is a guest post by Limor Maayan-Wainstein , a senior technical writer with 10 years of experience writing about cybersecurity, big data, cloud computing, web development, and more. High performance computing (HPC) enables you to solve complex problems which cannot be solved by regular computing.

Cloud 261

Cloud Big Data Virtualization Efficiency 261

DZone

FEBRUARY 1, 2023

Built on Azure Blob Storage, Azure Data Lake Storage Gen2 is a suite of features for big data analytics. Azure Data Lake Storage Gen1 and Azure Blob Storage's capabilities are combined in Data Lake Storage Gen2. For instance, Data Lake Storage Gen2 offers scale, file-level security, and file system semantics.

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Azure Storage Big Data Analytics 250

DZone

JUNE 13, 2023

The reason is straightforward, today, applications generate enormous amounts of data. As we embrace new technologies like cloud computing, big data analysis, and the Internet of Things (IoT), there is a noticeable spike in the amount of data generated from different applications.

Scalability 253

Scalability IoT Big Data Internet 253

DZone

JANUARY 19, 2023

Because with the advent of cloud providers, we are less worried about managing data centers. This leads to an increase in the size of data as well. Big data is generated and transported using various mediums in single requests. Everything is available within seconds on-demand.

Best Practices 262

Best Practices Transportation Big Data Latency 262

The Netflix TechBlog

JANUARY 13, 2022

This blog will explore these two systems and how they perform auto-diagnosis and remediation across our Big Data Platform and Real-time infrastructure. The streaming platform recently added Data Mesh , and we need to expand Streaming Pensive to cover that.

Big Data 243

Big Data Infrastructure Metrics Games 243

The Netflix TechBlog

JULY 15, 2021

I was later hired into my first purely data gig where I was able to deepen my knowledge of big data. After that, I joined MySpace back at its peak as a data engineer and got my first taste of data warehousing at internet-scale. In the data engineering space, very little of the same technology remains.

Data Engineering 200

Data Engineering Engineering Entertainment Big Data 200

DZone

JANUARY 31, 2023

Big data is at the center of all business decisions these days. It refers to large volumes of data generated through different sources, and this data then provides the foundation for business decisions. There are different ways through which we can process data.

Processing 241

Processing Big Data Systems 241

The Netflix TechBlog

OCTOBER 28, 2021

Netflix’s unique work culture and petabyte-scale data problems are what drew me to Netflix. During earlier years of my career, I primarily worked as a backend software engineer, designing and building the backend systems that enable big data analytics.

Data Engineering 183

Data Engineering Engineering Big Data Software Engineering 183

Dynatrace

MAY 1, 2023

Then, big data analytics technologies, such as Hadoop, NoSQL, Spark, or Grail, the Dynatrace data lakehouse technology, interpret this information. Here are the six steps of a typical ITOA process : Define the data infrastructure strategy. Why use a data lakehouse for causal AI? Why is ITOA important? Apache Spark.

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Analytics Artificial Intelligence Big Data Open Source 201

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., Microsoft’s big data clusters have 10s of thousands of machines, and are used by thousands of users to run some pretty complex queries. VLDB’19. For the larger more production-like query analysed in §4.2.1,

Big Data 57

Big Data Latency Analytics Azure 57

DZone

JULY 29, 2019

In today's world, data is generated in high volumes and to make something out of it, extracted data is needed to be transformed, stored, maintained, governed and analyzed. These processes are only possible with a distributed architecture and parallel processing mechanisms that Big Data tools are based on.

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Big Data Government Open Source Storage 162

The Netflix TechBlog

MARCH 25, 2019

Netflix’s diverse data landscape made it challenging to capture all the right data and conforming it to a common data model. Spark is the primary big-data compute engine at Netflix and with pretty much every upgrade in Spark, the spark plan changed as well springing continuous and unexpected surprises for us.

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Infrastructure Big Data Transportation Architecture 226

DZone

DECEMBER 21, 2020

Setting up a data warehouse is the first step towards fully utilizing big data analysis. Still, it is one of many that need to be taken before you can generate value from the data you gather. An important step in that chain of the process is data modeling and transformation.

Big Data 196

Big Data Google Scalability Processing 196

Dynatrace

JUNE 26, 2023

Software analytics offers the ability to gain and share insights from data emitted by software systems and related operational processes to develop higher-quality software faster while operating it efficiently and securely. This involves big data analytics and applying advanced AI and machine learning techniques, such as causal AI.

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Software Software Analytics Big Data 200

DZone

JANUARY 20, 2023

Having a distributed and scalable graph database system is highly sought after in many enterprise scenarios.

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Scalability Big Data Hardware Internet 210

The Netflix TechBlog

JULY 21, 2022

We at Netflix, as a streaming service running on millions of devices, have a tremendous amount of data about device capabilities/characteristics and runtime data in our big data platform. With large data, comes the opportunity to leverage the data for predictive and classification based analysis.

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Big Data Cache Engineering Data Engineering 190

DZone

JULY 22, 2022

Honestly, these two terms have recently been doing rounds in the big data world. These technologies specialize in transmitting large amounts of data across different trading partners and companies.

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Big Data Technology Technology Systems 188

DZone

FEBRUARY 6, 2024

If the data sources are not available then customized plugins can be developed to integrate these data sources. Grafana is used widely these days to monitor and visualize the metrics for 100s or 1000s of servers, Kubernetes Platforms, Virtual Machines, Big Data Platforms, etc.

Big Data 173

Big Data Open Source Virtualization Metrics 173

DZone

DECEMBER 28, 2020

Nowadays, Big Data tests mainly include data testing, paving the way for the Internet of Things to become the center point. Digital transformation is yet another significant focus point for the sectors and the enterprises that are ranking top on cloud and business analytics. Besides, AI and ML seem to reach a new level.

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Software Software Testing Big Data 193

DZone

DECEMBER 21, 2020

Applications used in the field of Big Data process huge amounts of information, and this often happens in real time. Naturally, such applications must be highly reliable so that no error in the code can interfere with data processing. It is an open-source framework for distributed processing of large amounts of data.

Code 159

Code Java Big Data Open Source 159

Dynatrace

OCTOBER 25, 2022

“AIOps platforms address IT leaders’ need for operations support by combining big data and machine learning functionality to analyze the ever-increasing volume, variety and velocity of data generated by IT in response to digital transformation.” – Gartner Market Guide for AIOps platforms.

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DevOps Big Data Cloud Innovation 229

The Netflix TechBlog

APRIL 29, 2019

Orchestration The Big Data Orchestration team is responsible for providing all of the services and tooling to schedule and execute ETL and Adhoc pipelines. These libraries are the primary way users interface programmatically with work in the Big Data platform.

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Open Source Network Infrastructure Big Data 280

Dynatrace

AUGUST 10, 2021

She dispelled the myth that more big data equals better decisions, higher profits, or more customers. Investing in data is easy but using it is really hard”. The fact is, data on its own isn’t meaningful. Tricia quoted the statistic that companies typically use 3% of their data to inform decisions.

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DevOps Big Data Innovation Cloud 246

DZone

AUGUST 23, 2023

In the era of big data, efficient data management and query performance are critical for organizations that want to get the best operational performance from their data investments.

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Big Data Analytics Innovation Scalability 130

The Netflix TechBlog

OCTOBER 27, 2020

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The processed data is typically stored as data warehouse tables in AWS S3.

Latency 254

Latency Storage Big Data Tuning 254

The Netflix TechBlog

JULY 26, 2021

However, it is paramount that we validate the complete set of identifiers such as a list of movie ids across producers and consumers for higher overall confidence in the data transport layer of choice. The audits check for equality (i.e.

Big Data 258

Big Data Government Processing Analytics 258

Dynatrace

OCTOBER 4, 2022

While data lakehouses combine the flexibility and cost-efficiency of data lakes with the querying capabilities of data warehouses, it’s important to understand how these storage environments differ. Data warehouses. Data warehouses were the original big data storage option.

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Artificial Intelligence Storage Analytics Government 221