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. Dynamic approaches schedule block processing on the fly to maximise efficiency. ACM Computing Surveys, Dec.

Big Data 83

Big Data Open Source Processing Analytics 83

The Morning Paper

SEPTEMBER 8, 2019

Experiences with approximating queries in Microsoft’s production big-data clusters Kandula et al., I’ve been excited about the potential for approximate query processing in analytic clusters for some time, and this paper describes its use at scale in production. The accuracy was considered adequate by the developer.

Big Data 57

Big Data Analytics Latency Azure 57

Dynatrace

JULY 6, 2022

Ultimately, IT automation can deliver consistency, efficiency, and better business outcomes for modern enterprises. Automating IT practices offers enterprises faster data centers and cloud operations, as well as increased flexibility and accuracy. Developing automation takes time. Big data automation tools.

Artificial Intelligence 198

Artificial Intelligence Tuning Strategy Big Data 198

Dynatrace

OCTOBER 25, 2022

The need for developers and innovation is now even greater. NoOps is a concept in software development that seeks to automate processes and eliminate the need for an extensive IT operations team. But it might also result in the entire software development process falling apart. Evolution of modern AIOps.

DevOps 225

DevOps Big Data Cloud Innovation 225

Dynatrace

JULY 5, 2022

AIOps combines big data and machine learning to automate key IT operations processes, including anomaly detection and identification, event correlation, and root-cause analysis. A truly modern AIOps solution also serves the entire software development lifecycle to address the volume, velocity, and complexity of multicloud environments.

Artificial Intelligence 295

Artificial Intelligence Cloud Innovation Strategy 295

Scalegrid

MARCH 14, 2024

In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently. Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Scalegrid

MARCH 28, 2024

However, its limited feature set compared to Redis might be a disadvantage for applications that require more advanced data structures and persistence. Introduction Caching serves a dual purpose in web development – speeding up client requests and reducing server load.

Cache 130

Cache Storage Scalability Architecture 130

The Netflix TechBlog

SEPTEMBER 18, 2020

Part of our series on who works in Analytics at Netflix?—?and and what the role entails by Julie Beckley & Chris Pham This Q&A provides insights into the diverse set of skills, projects, and culture within Data Science and Engineering (DSE) at Netflix through the eyes of two team members: Chris Pham and Julie Beckley.

Analytics 223

Analytics Education Innovation Engineering 223

Dynatrace

DECEMBER 15, 2022

We’ll discuss how the responsibilities of ITOps teams changed with the rise of cloud technologies and agile development methodologies. Adding application security to development and operations workflows increases efficiency. So, what is ITOps? What is ITOps? ITOps vs. AIOps. ” The post What is ITOps?

Artificial Intelligence 211

Artificial Intelligence DevOps Hardware Virtualization 211

Dynatrace

MARCH 24, 2023

By embracing public cloud and hybrid cloud computing environments, IT teams can further accelerate development and automate software deployment and management. Container technology enables organizations to efficiently develop cloud-native applications or to modernize legacy applications to take advantage of cloud services.

Infrastructure 195

Infrastructure Open Source Operating System Cloud 195

The Netflix TechBlog

JUNE 7, 2021

By Alok Tiagi , Hariharan Ananthakrishnan , Ivan Porto Carrero and Keerti Lakshminarayan Netflix has developed a network observability sidecar called Flow Exporter that uses eBPF tracepoints to capture TCP flows at near real time. The data is also used by security and other partner teams for insight and incident analysis.

Network 325

Network Transportation AWS Cloud 325

Dynatrace

OCTOBER 17, 2022

Artificial intelligence for IT operations, or AIOps, combines big data and machine learning to provide actionable insight for IT teams to shape and automate their operational strategy. This makes developing, operating, and securing modern applications and the environments they run on practically impossible without AI.

DevOps 205

DevOps Artificial Intelligence Healthcare Innovation 205

Dynatrace

JULY 6, 2020

As adoption rates for Microsoft Azure continue to skyrocket, Dynatrace is developing a deeper integration with the platform to provide even more value to organizations that run their businesses on Azure or use it as a part of their multi-cloud strategy. See the health of your big data resources at a glance. Azure Front Door.

Azure 151

Azure Cloud Big Data Virtualization 151

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. Analysis of such large data sets often requires powerful distributed data stores like Hadoop and heavy data processing with techniques like MapReduce.

Analytics 191

Analytics Traffic Big Data Efficiency 191

The Netflix TechBlog

MARCH 2, 2021

At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group. & Wenjing Z.]

Analytics 207

Analytics C++ Innovation Engineering 207

Dynatrace

OCTOBER 14, 2021

Gartner defines AIOps as the combination of “big data and machine learning to automate IT operations processes, including event correlation, anomaly detection, and causality determination.” Only deterministic AIOps technology enables fully automated cloud operations across the entire enterprise development lifecycle.

Artificial Intelligence 221

Artificial Intelligence DevOps Innovation Metrics 221

KeyCDN

OCTOBER 2, 2018

In the world of web development, those who become experts usually do so by learning from their predecessors. Reading and following the right web development blogs makes it much easier to get a solid education. That’s why we’ve compiled an exhaustive list of web development blogs and newsletters to make this process easier.

Development 75

Development Website Design Code 75

ScaleOut Software

NOVEMBER 24, 2020

Rapid advances in the telematics industry have dramatically boosted the efficiency of vehicle fleets and have found wide ranging applications from long haul transport to usage-based insurance. Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Testsigma

FEBRUARY 12, 2021

With the latest developments in IT sector services, the sector of QA testing has seen significant improvement and growth. The implementation of emerging technologies has helped improve the process of software development, testing, design and deployment. Gartner’s 2020 projections first included the trend of hyperautomation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

All Things Distributed

DECEMBER 20, 2017

Developments like cloud computing, the internet of things, artificial intelligence, and machine learning are proving that IT has (again) become a strategic business driver. Kärcher benefits as well: By developing this service, the company gets exact insight into how the machines are actually used by its customers.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

The Morning Paper

SEPTEMBER 19, 2019

AliGraph covers Alibaba’s distributed graph engine supporting the development of new GNN applications. Their dataset has about 7B edges… Meanwhile, AnalyticDB is Alibaba’s real-time OLAP RDBMS handling 10PB of data (in excess of 100 trillion rows!). .” Could it be Analyzing efficient stream processing on modern hardware ?

Blockchain 46

Blockchain Hardware Google Analytics 46

All Things Distributed

JUNE 29, 2011

AWS also applies the same customer oriented pricing strategy: as the AWS platform grows, our scale enables us to operate more efficiently, and we choose to pass the benefits back to customers in the form of cost savings. Driving down the cost of Big-Data analytics. blog comments powered by Disqus. Contact Info.

AWS 104

AWS Retail Innovation Strategy 104

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. It is a high-risk process because the sensitive data of customers’ is at stake. Data subset creation.

Testing 60

Testing Storage Database Processing 60

The Netflix TechBlog

JULY 26, 2021

The paradigm spans across methods, tools, and technologies and is usually defined in contrast to analytical reporting and predictive modeling which are more strategic (vs. At Netflix Studio, teams build various views of business data to provide visibility for day-to-day decision making. tactical) in nature.

Big Data 253

Big Data Government Analytics Processing 253

Highly Scalable

MARCH 10, 2015

Although there are many books on data mining in general and its applications to marketing and customer relationship management in particular [BE11, AS14, PR13 etc.], The rest of the article is organized as follows: We first introduce a simple framework that ties together a retailer’s actions, profits and data.

Retail 152

Retail C++ Analytics Metrics 152

The Netflix TechBlog

APRIL 29, 2019

Subsequently, many useful libraries get developed, making the language even more desirable to learn and use. Demand Engineering Demand Engineering is responsible for Regional Failovers , Traffic Distribution, Capacity Operations and Fleet Efficiency of the Netflix cloud. But Python plays a huge role in how we provide those services.

Open Source 279

Open Source Network Infrastructure Big Data 279

The Netflix TechBlog

NOVEMBER 20, 2023

We will show how we are building a clean and efficient incremental processing solution (IPS) by using Netflix Maestro and Apache Iceberg. IPS provides the incremental processing support with data accuracy, data freshness, and backfill for users and addresses many of the challenges in workflows. past 3 hours or 10 days).

Processing 210

Processing Big Data Efficiency Engineering 210

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. Therefore, we must efficiently move data from the data warehouse to a global, low-latency and highly-reliable key-value store.

Latency 243

Latency Storage Big Data Tuning 243

All Things Distributed

DECEMBER 13, 2009

The broad Amazon EC2 customer base brings such diversity in workload and utilization patterns that it allows us to operate Amazon EC2 with extreme efficiency. A highly efficient purchasing model such as Spot Instances is another way in which Amazon EC2 customers benefit from the unique economies of scale found in AWS Infrastructure Services.

Cloud 63

Cloud AWS Storage Innovation 63

All Things Distributed

DECEMBER 13, 2016

With the launch of the AWS Europe (London) Region, AWS can enable many more UK enterprise, public sector and startup customers to reduce IT costs, address data locality needs, and embark on rapid transformations in critical new areas, such as big data analysis and Internet of Things. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

Smashing Magazine

JULY 29, 2019

I hope to raise the profile of difficulties faced by real people, which are avoidable if we design and develop in a way that is sympathetic to their needs. Notice the async keyword on the Google analytics script? Google analytics has ‘low’ priority. Read “ Efficiently load JavaScript with defer and async ” for more information.

Cache 96

Cache Google Mobile Network 96

Abhishek Tiwari

DECEMBER 27, 2017

A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. It offers reliability and performance of a data warehouse, real-time and low-latency characteristics of a streaming system, and scale and cost-efficiency of a data lake.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

All Things Distributed

MAY 21, 2018

We already have an idea of how digitalization, and above all new technologies like machine learning, big-data analytics or IoT, will change companies' business models — and are already changing them on a wide scale. At the end of 2018, voice (input) will have already significantly changed the way we develop devices and apps.

Artificial Intelligence 76

Artificial Intelligence Technology Technology IoT 76

All Things Distributed

NOVEMBER 15, 2010

Now that our ability to generate higher and higher clock rates has stalled and CPU architectural improvements have shifted focus towards multiple cores, we see that it is becoming harder to efficiently use these computer systems. Â The input data is often organized as a Grid.

AWS 136

AWS Latency Programming Architecture 136