Dynatrace

DECEMBER 21, 2023

A business process is a collection of related, usually structured tasks or steps, performed in sequence, that achieve a defined business goal. Tasks may be manual or automatic, and many business processes will include a combination of both. Make better decisions by providing managers with real-time data about the business.

Processing 217

Processing Monitoring Retail Analytics 217

DZone

JULY 13, 2023

In today's data-driven world, organizations need efficient and scalable data pipelines to process and analyze large volumes of data. Medallion Architecture provides a framework for organizing data processing workflows into different zones, enabling optimized batch and stream processing.

Azure 246

Azure Architecture Efficiency Processing 246

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. What Is Batch Processing?

Processing 235

Processing Big Data Systems 235

Dynatrace

APRIL 22, 2024

To enable participating organizations to meet the EU requirements for transferring personal data to the U.S., the Data Privacy Framework (DPF) is designed to serve as an adequate data transfer mechanism under the GDPR. Data Privacy Framework Program (The EU-U.S. Benefits of Data Privacy Framework for Dynatrace customers.

Government 203

Government Programming Analytics Efficiency 203

Dynatrace

FEBRUARY 9, 2024

Recent platform enhancements in the latest Dynatrace, including business events powered by Grail™, make accessing the goldmine of business data flowing through your IT systems easier than ever. The Business Flow app Business Flow, built with AppEngine, simplifies the configuration, monitoring, and analysis of business processes.

Processing 194

Processing Monitoring Analytics Games 194

Dynatrace

AUGUST 16, 2022

The data locked in your log files can be a goldmine for your application developers, operations teams, and your enterprise as a whole. However, it can be complicated , expensive , or even impossible to set up robust observability that makes use of this data. Log format inconsistency makes it a challenge to access critical data.

Processing 193

Processing Metrics Monitoring Java 193

Dynatrace

MARCH 15, 2024

As organizations strive for observability and data democratization, OpenTelemetry emerges as a key technology to create and transfer observability data. Understanding OpenTelemetry OpenTelemetry is an open, vendor-neutral standard for creating, collecting, and transferring telemetry data, like traces, metrics, and logs.

Open Source 287

Open Source Best Practices Infrastructure Tuning 287

DZone

MARCH 31, 2023

In the digital age, data is the new currency and is being used everywhere. From social media to IoT devices, businesses are generating more data than ever before. With this data comes the challenge of processing it in a timely and efficient way. Let’s recap some of the basics first.

Processing 234

Processing Social Media IoT Media 234

The Netflix TechBlog

DECEMBER 14, 2023

Engineers from across the company came together to share best practices on everything from Data Processing Patterns to Building Reliable Data Pipelines. The result was a series of talks which we are now sharing with the rest of the Data Engineering community!

Data Engineering 259

Data Engineering Engineering Software Engineering Best Practices 259

DZone

JANUARY 8, 2024

Financial data engineering in SAS involves the management, processing, and analysis of financial data using the various tools and techniques provided by the SAS software suite. Here are some key aspects of financial data engineering in SAS: 1.

Data Engineering 278

Data Engineering Engineering Database Software 278

DZone

NOVEMBER 7, 2023

In the rapidly evolving digital landscape, the role of data has shifted from being merely a byproduct of business to becoming its lifeblood. With businesses constantly in the race to stay ahead, the process of integrating this data becomes crucial.

Systems 281

Systems Analytics Architecture Engineering 281

DZone

NOVEMBER 30, 2023

It uses Python as its programming language and offers a flexible architecture suited for both small-scale and large-scale data processing. The platform supports the concept of Directed Acyclic Graphs to define workflows, making it easy to visualize complex data pipelines.

Processing 161

Processing Open Source Programming Architecture 161

The Netflix TechBlog

NOVEMBER 14, 2023

By Abhinaya Shetty , Bharath Mummadisetty At Netflix, our Membership and Finance Data Engineering team harnesses diverse data related to plans, pricing, membership life cycle, and revenue to fuel analytics, power various dashboards, and make data-informed decisions. We expect complete and accurate data at the end of each run.

Data Engineering 264

Data Engineering Engineering Processing Games 264

Dynatrace

FEBRUARY 28, 2024

In a digital-first world, site reliability engineers and IT data analysts face numerous challenges with data quality and reliability in their quest for cloud control. Increasingly, organizations seek to address these problems using AI techniques as part of their exploratory data analytics practices.

Analytics 215

Analytics Metrics Media Monitoring 215

DZone

NOVEMBER 20, 2023

ETL—Extract, Transform, Load—is far more than a set of operations; it's a complex dance that transforms raw data into valuable insights, serving as the critical backbone for a range of applications, from data analytics and business intelligence to real-time decision-making platforms. What makes ETL performance such an imperative?

Processing 117

Processing Performance Analytics Speed 117

The Netflix TechBlog

MARCH 10, 2023

This platform has evolved from supporting studio applications to data science applications, machine-learning applications to discover the assets metadata, and build various data facts. Hence we built the data pipeline that can be used to extract the existing assets metadata and process it specifically to each new use case.

Media 237

Media Traffic Processing Design 237

High Scalability

JUNE 15, 2020

This is a guest post by Eunice Do , Data Engineer at TripleLift , a technology company leading the next generation of programmatic advertising. The system is the data pipeline at TripleLift. TripleLift is an adtech company, and like most companies in this industry, we deal with high volumes of data on a daily basis.

Processing 206

Processing Data Engineering Efficiency Engineering 206

Dynatrace

OCTOBER 4, 2022

For IT infrastructure managers and site reliability engineers, or SREs , logs provide a treasure trove of data. But on their own, logs present just another data silo as IT professionals attempt to troubleshoot and remediate problems. Data volume explosion in multicloud environments poses log issues.

Analytics 226

Analytics Storage Infrastructure Metrics 226

DZone

APRIL 11, 2023

Data processing in the cloud has become increasingly popular due to its scalability, flexibility, and cost-effectiveness. This article will explore how these technologies can be used together to create an optimized data pipeline for data processing in the cloud.

Azure 246

Azure Analytics Storage Cloud 246

Dynatrace

JANUARY 31, 2024

I have ingested important custom data into Dynatrace, critical to running my applications and making accurate business decisions… but can I trust the accuracy and reliability?” ” Welcome to the world of data observability. At its core, data observability is about ensuring the availability, reliability, and quality of data.

DevOps 197

DevOps Analytics Airlines Metrics 197

Dynatrace

JANUARY 4, 2024

While this approach can be effective if the model is trained with a large amount of data, even in the best-case scenarios, it amounts to an informed guess, rather than a certainty. But to be successful, data quality is critical. Teams need to ensure the data is accurate and correctly represents real-world scenarios. Consistency.

Government 204

Government Analytics Benchmarking Storage 204

DZone

MAY 12, 2023

I believe that chief among them is d ata residency or data location: Data localization or data residency law requires data about a nation's citizens or residents to be collected, processed, and/or stored inside the country, often before being transferred internationally.

Cloud 242

Cloud Systems Processing 242

DZone

AUGUST 23, 2023

Monitoring Time-Series IoT Device Data Time-series data is crucial for IoT device monitoring and data visualization in industries such as agriculture, renewable energy, and meteorology. In this tutorial, we will guide you through the process of setting up a monitoring system for IoT device data.

IoT 241

IoT Energy Open Source Analytics 241

Dynatrace

MARCH 15, 2024

As organizations strive for observability and data democratization, OpenTelemetry emerges as a key technology to create and transfer observability data. Understanding OpenTelemetry OpenTelemetry is an open, vendor-neutral standard for creating, collecting, and transferring telemetry data, like traces, metrics, and logs.

Open Source 130

Open Source Best Practices Infrastructure Tuning 130

DZone

AUGUST 18, 2023

We all know that data is being generated at an unprecedented rate. You may also know that this has led to an increase in the demand for efficient and secure data storage solutions that won’t break the bank. This article will explore what edge data platforms and real-time services are, why they are important, and how they can be used.

IoT 130

IoT Media Latency Storage 130

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. What is a data lakehouse? How does a data lakehouse work?

Artificial Intelligence 213

Artificial Intelligence Analytics Storage Government 213

Scalegrid

JANUARY 5, 2024

Enhanced data security, better data integrity, and efficient access to information. This article cuts through the complexity to showcase the tangible benefits of DBMS, equipping you with the knowledge to make informed decisions about your data management strategies. What are the key advantages of DBMS?

Efficiency 147

Efficiency Storage Database Scalability 147

Scalegrid

JANUARY 19, 2024

When a MongoDB rollback happens, it can cause trouble to your data integrity and system consistency. Understanding how to address a rollback is critical for minimizing potential data loss and maintaining seamless operations. With direct, actionable insights, prepare to navigate the complexities of rollbacks with confidence.

Database 130

Database Network Servers Monitoring 130

Dynatrace

JANUARY 23, 2024

AI data analysis can help development teams release software faster and at higher quality. So how can organizations ensure data quality, reliability, and freshness for AI-driven answers and insights? And how can they take advantage of AI without incurring skyrocketing costs to store, manage, and query data?

Performance 190

Performance DevOps Innovation Artificial Intelligence 190

Dynatrace

APRIL 19, 2023

Creating an ecosystem that facilitates data security and data privacy by design can be difficult, but it’s critical to securing information. When organizations focus on data privacy by design, they build security considerations into cloud systems upfront rather than as a bolt-on consideration.

Design 196

Design Storage Programming Analytics 196

Dynatrace

JUNE 9, 2023

ln a world driven by macroeconomic uncertainty, businesses increasingly turn to data-driven decision-making to stay agile. They’re unleashing the power of cloud-based analytics on large data sets to unlock the insights they and the business need to make smarter decisions. All of these factors challenge DevOps maturity.

DevOps 188

DevOps Analytics Storage Metrics 188

DZone

MARCH 29, 2023

Data migration is the process of moving data from one location to another, which is an essential aspect of cloud migration. Data migration involves transferring data from on-premise storage to the cloud. With the rapid adoption of cloud computing , businesses are moving their IT infrastructure to the cloud.

Best Practices 304

Best Practices Cloud Storage Data Engineering 304

DZone

AUGUST 10, 2023

Many modern applications have a batch processing aspect to them and regularly run high-volume, repetitive data jobs. Here are the four tactics for cost-efficient and resilient batch processing: Here are the four tactics for cost-efficient and resilient batch processing:

Efficiency 130

Efficiency Processing Cloud Technology 130

The Netflix TechBlog

JANUARY 13, 2022

By Vikram Srivastava and Marcelo Mayworm Netflix has one of the most complex data platforms in the cloud on which our data scientists and engineers run batch and streaming workloads. As our subscribers grow worldwide and Netflix enters the world of gaming , the number of batch workflows and real-time data pipelines increases rapidly.

Big Data 238

Big Data Infrastructure Metrics Hardware 238

Dynatrace

OCTOBER 4, 2022

Some time ago, at a restaurant near Boston, three Dynatrace colleagues dined and discussed the growing data challenge for enterprises. At its core, this challenge involves a rapid increase in the amount—and complexity—of data collected within a company. Work with different and independent data types. Thus, Grail was born.

Artificial Intelligence 272

Artificial Intelligence Analytics Storage Architecture 272

Scalegrid

MAY 13, 2020

Greenplum Database is a massively parallel processing (MPP) SQL database that is built and based on PostgreSQL. It can scale towards a multi-petabyte level data workload without a single issue, and it allows access to a cluster of powerful servers that will work together within a single SQL interface where you can view all of the data.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

Dynatrace

SEPTEMBER 14, 2022

As an industry leader, Dynatrace promotes primarily using software and AI to deal with this complexity at scale instead of just putting data on dashboards. Does that mean that reactive and exploratory data analysis, often done manually and with the help of dashboards, are dead? Why today’s data analytics solutions still fail us.

Metrics 234

Metrics Analytics Monitoring Efficiency 234