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. Open source ER systems.

Big Data 83

Big Data Open Source Processing Analytics 83

All Things Distributed

AUGUST 18, 2011

Werner Vogels weblog on building scalable and robust distributed systems. 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.

Big Data 112

Big Data Analytics AWS Scalability 112

Scalegrid

MARCH 14, 2024

Understanding Hybrid Cloud Strategy A hybrid cloud merges the capabilities of public and private clouds into a singular, coherent system. This combination allows for the fluid movement of data and applications across different environments, facilitating shared workloads seamlessly.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

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. IT automation tools can achieve enterprise-wide efficiency.

Artificial Intelligence 188

Artificial Intelligence Tuning Strategy Big Data 188

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. ICDE’16 (PowerDrill is a Google internal system).

Big Data 57

Big Data Analytics Latency Azure 57

Scalegrid

MARCH 28, 2024

Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup. On the other hand, an append-only file ensures data safety by recording every write operation that modifies the dataset, allowing for complete data reconstruction in the event of a restart. Data transfer technology.

Cache 130

Cache Storage Scalability Architecture 130

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. Like the development and design phases, these applications generate massive data volumes that offer relevant and actionable insights.

Artificial Intelligence 285

Artificial Intelligence Cloud Innovation Strategy 285

Dynatrace

OCTOBER 25, 2022

Organizations adopt DevOps, where developers and operations work together in a continuous loop, so they can develop software and resolve issues efficiently before they affect users. Early implementations of NoOps were just ‘lift and shift’ efforts that replicated existing systems to the cloud. Evolution of NoOps.

DevOps 217

DevOps Big Data Cloud Innovation 217

Dynatrace

DECEMBER 15, 2022

In fact, Gartner estimates that 80% of enterprises will shut down their on-premises data centers by 2025. This transition to public, private, and hybrid cloud is driving organizations to automate and virtualize IT operations to lower costs and optimize cloud processes and systems. So, what is ITOps? Why is IT operations important?

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

Dynatrace

MARCH 24, 2023

Containers enable developers to package microservices or applications with the libraries, configuration files, and dependencies needed to run on any infrastructure, regardless of the target system environment. This means organizations are increasingly using Kubernetes not just for running applications, but also as an operating system.

Infrastructure 185

Infrastructure Open Source Operating System Cloud 185

The Netflix TechBlog

JUNE 7, 2021

Cloud Network Insight is a suite of solutions that provides both operational and analytical insight into the cloud network infrastructure to address the identified problems. 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. The four stages of data processing. This process continues until the system identifies a root cause.

DevOps 195

DevOps Artificial Intelligence Healthcare Innovation 195

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

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. User Experience and Business Analytics ery user journey and maximize business KPIs.

Artificial Intelligence 182

Artificial Intelligence Social Media Monitoring IoT 182

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.” This contrasts stochastic AIOps approaches that use probability models to infer the state of systems. What is AIOps?

Artificial Intelligence 212

Artificial Intelligence DevOps Innovation Metrics 212

Dynatrace

JUNE 1, 2020

The variables that can impact the performance of an application vary; from coding errors or ‘bugs’ in the software, database slowdowns, hosting and network performance, to operating system and device type support. User Experience and Business Analytics ery user journey and maximize business KPIs.

Monitoring 132

Monitoring Performance Social Media Artificial Intelligence 132

ScaleOut Software

NOVEMBER 24, 2020

Real-Time Digital Twins Can Add Important New Capabilities to Telematics Systems and Eliminate Scalability Bottlenecks. 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.

Analytics 52

Analytics Architecture Scalability Software Architecture 52

Tech News Gather

OCTOBER 7, 2023

Enhance Call Routing and Response Times Efficient call routing and quick response times are crucial for customer satisfaction. With this data, you can implement intelligent call routing systems that ensure calls are directed to the right department or agent, reducing wait times and improving the overall customer experience.

Strategy 52

Strategy Big Data Scalability Games 52

The Morning Paper

SEPTEMBER 19, 2019

” Crusher is a Google system for automatically discovering email templates (e.g. Could it be Analyzing efficient stream processing on modern hardware ? On one of the themes that captures my imagination, how changing hardware platform influence system design: Rethinking database high availability with RDMA networks.

Blockchain 46

Blockchain Hardware Google Analytics 46

Testsigma

FEBRUARY 12, 2021

The usage by advanced techniques such as RPA, Artificial Intelligence, machine learning and process mining is a hyper-automated application that improves employees and automates operations in a way which is considerably more efficient than conventional automation. Gartner’s 2020 projections first included the trend of hyperautomation.

Artificial Intelligence 92

Artificial Intelligence Software Software IoT 92

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. However, ClickHouse is super efficient for timeseries and provides “sharding” out of the box (scalability beyond one node).

Database 40

Database Analytics Blockchain Healthcare 40

All Things Distributed

DECEMBER 20, 2017

For example, Kärcher, the maker of cleaning technologies, manages its entire fleet through the cloud solution "Kärcher Fleet" This transmits data from the company's cleaning devices e.g. about the status of maintenance and loading, when the machines are used, and where the machines are located. This pattern should be broken.

Artificial Intelligence 79

Artificial Intelligence Social Media Logistics AWS 79

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. The test data management for the company had become a big problem and had to be solved.

Testing 60

Testing Storage Database Processing 60

All Things Distributed

JUNE 29, 2011

Werner Vogels weblog on building scalable and robust distributed systems. 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. All Things Distributed. Comments ().

AWS 106

AWS Retail Innovation Strategy 106

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

JULY 26, 2021

This happens at an unprecedented scale and introduces many interesting challenges; one of the challenges is how to provide visibility of Studio data across multiple phases and systems to facilitate operational excellence and empower decision making. tactical) in nature. Currently Iceberg sink is appended only.

Big Data 253

Big Data Government Analytics Processing 253

The Netflix TechBlog

APRIL 29, 2019

Various software systems are needed to design, build, and operate this CDN infrastructure, and a significant number of them are written in Python. The configuration of these devices is controlled by several other systems including source of truth, application of configurations to devices, and back up.

Open Source 279

Open Source Network Infrastructure Big Data 279

KeyCDN

OCTOBER 2, 2018

It’s awesome for discovering how grid systems, CSS animation, Big Data, etc all play roles in real-world web design. Subjects like version control, crowdfunding, database selection and code editor choices are essential to efficient modern workflows, and this is a good place to start learning about them.

Development 75

Development Website Design Code 75

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

Werner Vogels weblog on building scalable and robust distributed systems. 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. Driving down the cost of Big-Data analytics. All Things Distributed. Comments ().

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

Abhishek Tiwari

DECEMBER 27, 2017

Unified data management architecture. A unified data management (UDM) system combines the best of data warehouses, data lakes, and streaming without expensive and error-prone ETL. For instance, Alluxio, originally known as Tachyon, can potentially use Arrow as its in-memory data structure.

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. Which human activities can be taken over by machines or ML-based systems? The workplace of the future.

Artificial Intelligence 77

Artificial Intelligence Technology Technology IoT 77

All Things Distributed

NOVEMBER 15, 2010

Werner Vogels weblog on building scalable and robust distributed systems. 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. All Things Distributed.

AWS 136

AWS Latency Programming Architecture 136