Dynatrace

NOVEMBER 29, 2024

By ensuring that all processes—from data collection to storage and usage—comply with regulatory requirements, organizations can better manage potential threats. Retention periods and access controls must be properly configured to protect such PII. Want to learn more?

Healthcare 237

Healthcare Analytics Storage Government 237

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.

Azure 250

Azure Storage Big Data Analytics 250

Dynatrace

NOVEMBER 18, 2024

The Grail™ data lakehouse provides fast, auto-indexed, schema-on-read storage with massively parallel processing (MPP) to deliver immediate, contextualized answers from all data at scale. Through Azure Native Dynatrace Service, customers can seamlessly adopt these technologies to modernize and enhance their cloud operations.

Cloud 263

Cloud Azure Artificial Intelligence Innovation 263

Dynatrace

OCTOBER 4, 2022

Log management and analytics is an essential part of any organization’s infrastructure, and it’s no secret the industry has suffered from a shortage of innovation for several years. Teams have introduced workarounds to reduce storage costs. Current analytics tools are fragmented and lack context for meaningful analysis.

Analytics 264

Analytics Artificial Intelligence Storage Serverless 264

Dynatrace

AUGUST 20, 2024

Information related to user experience, transaction parameters, and business process parameters has been an unretrieved treasure, now accessible through new and unique AI-powered contextual analytics in Dynatrace. Executives drive business growth through strategic decisions, relying on data analytics for crucial insights.

Analytics 285

Analytics Latency Processing Systems 285

Dynatrace

JULY 29, 2022

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 246

Analytics Storage Retail DevOps 246

Dynatrace

JULY 29, 2022

What is log analytics? Log analytics is the process of viewing, interpreting, and querying log data so developers and IT teams can quickly detect and resolve application and system issues. In what follows, we explore log analytics benefits and challenges, as well as a modern observability approach to log analytics.

Analytics 245

Analytics Storage Retail DevOps 245

Dynatrace

OCTOBER 4, 2022

Traditionally, though, to gain true business insight, organizations had to make tradeoffs between accessing quality, real-time data and factors such as data storage costs. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. Enter Grail-powered data and analytics.

Analytics 246

Analytics Software Software Storage 246

Dynatrace

MARCH 6, 2024

The latest Dynatrace report, “ The state of observability 2024: Overcoming complexity through AI-driven analytics and automation ,” explores these challenges and highlights how IT, business, and security teams can overcome them with a mature AI, analytics, and automation strategy.

Analytics 246

Analytics Innovation Strategy Storage 246

Dynatrace

NOVEMBER 15, 2021

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. What is log analytics? Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.

Analytics 264

Analytics Monitoring DevOps Artificial Intelligence 264

Dynatrace

FEBRUARY 2, 2023

Exploding volumes of business data promise great potential; real-time business insights and exploratory analytics can support agile investment decisions and automation driven by a shared view of measurable business goals. Traditional observability solutions don’t capture or analyze application payloads. What’s next?

Analytics 246

Analytics Metrics DevOps Storage 246

Dynatrace

JULY 29, 2021

With extended contextual analytics and AIOps for open observability, Dynatrace now provides you with deep insights into every entity in your IT landscape, enabling you to seamlessly integrate metrics, logs, and traces—the three pillars of observability. Dynatrace extends its unique topology-based analytics and AIOps approach.

Analytics 246

Analytics Open Source Serverless Architecture 246

Dynatrace

JANUARY 12, 2022

Messaging systems are typically implemented as lightweight storage represented by queues or topics. We’ve introduced brand-new analytics capabilities by building on top of existing features for messaging systems. The post New analytics capabilities for messaging system-related anomalies appeared first on Dynatrace blog.

Analytics 246

Analytics Systems DevOps Healthcare 246

Dynatrace

AUGUST 9, 2023

A traditional log-based SIEM approach to security analytics may have served organizations well in simpler on-premises environments. Security Analytics and automation deal with unknown-unknowns With Security Analytics, analysts can explore the unknown-unknowns, facilitating queries manually in an ad hoc way, or continuously using automation.

Analytics 246

Analytics Metrics Database Storage 246

Dynatrace

JANUARY 31, 2024

By putting data in context, OpenPipeline enables the Dynatrace platform to deliver AI-driven insights, analytics, and automation for customers across observability, security, software lifecycle, and business domains. This “data in context” feeds Davis® AI, the Dynatrace hypermodal AI , and enables schema-less and index-free analytics.

Analytics 272

Analytics Processing Transportation Storage 272

Dynatrace

FEBRUARY 12, 2024

With unified observability and security, organizations can protect their data and avoid tool sprawl with a single platform that delivers AI-driven analytics and intelligent automation. Grail handles data storage, data management, and processes data at massive speed, scale, and cost efficiency,” Singh said. This is Davis CoPilot.

Analytics 245

Analytics Artificial Intelligence Engineering Technology 245

Scalegrid

FEBRUARY 6, 2025

Kafka is optimized for high-throughput event streaming , excelling in real-time analytics and large-scale data ingestion. Message brokers handle validation, routing, storage, and delivery, ensuring efficient and reliable communication. This decoupling simplifies system architecture and supports scalability in distributed environments.

Latency 147

Latency Analytics Architecture Storage 147

Scalegrid

MAY 13, 2020

Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. This feature-packed database provides powerful and rapid analytics on data that scales up to petabyte volumes. What Exactly is Greenplum? At a glance – TLDR.

Big Data 321

Big Data Database Artificial Intelligence Open Source 321

DZone

APRIL 11, 2023

Modern tech stacks such as Apache Spark, Azure Data Factory, Azure Databricks, and Azure Synapse Analytics offer powerful tools for building optimized data pipelines that can efficiently ingest and process data on the cloud. It provides built-in connectors for various data sources such as databases, file systems, cloud storage, and more.

Azure 246

Azure Analytics Storage Cloud 246

DZone

FEBRUARY 10, 2025

Microsoft Azure SQL is a robust, fully managed database platform designed for high-performance querying, relational data storage, and analytics. An application software generates user metrics on a daily basis, which can be used for reports or analytics.

Metrics 165

Metrics Azure Analytics Storage 165

Dynatrace

FEBRUARY 24, 2025

But even the best BPM solutions lack the IT context to support actionable process analytics; this is the opportunity for observability platforms. Transaction metadata (such as a product SKU, loan amount, or service address) enriches process insights and increases analytic granularity.

Processing 147

Processing Analytics Infrastructure Monitoring 147

Dynatrace

FEBRUARY 16, 2023

Grail combines the big-data storage of a data warehouse with the analytical flexibility of a data lake. With Grail, we have reinvented analytics for converged observability and security data,” Greifeneder says. Logs on Grail Log data is foundational for any IT analytics. Grail and DQL will give you new superpowers.”

Analytics 246

Analytics Innovation Metrics Database 246

The Netflix TechBlog

FEBRUARY 14, 2025

Analytical Insights Additionally, impression history offers insightful information for addressing a number of platform-related analytics queries. The enriched data is seamlessly accessible for both real-time applications via Kafka and historical analysis through storage in an Apache Iceberg table.

Tuning 165

Tuning Latency Efficiency Storage 165

Dynatrace

OCTOBER 7, 2020

This gives you all the benefits of a metric storage system, including exploring and charting metrics, building dashboards, and alerting on anomalies. The post Intelligent, context-aware AI analytics for all your custom metrics appeared first on Dynatrace blog.

Metrics 246

Metrics Analytics Storage Monitoring 246

Dynatrace

FEBRUARY 9, 2021

As an application owner, product manager, or marketer, however, you might use analytics tools like Adobe Analytics to understand user behavior, user segmentation, and strategic business metrics such as revenue, orders, and conversion goals. Enable the storage types, select Add property.

Analytics 208

Analytics Mobile Airlines Monitoring 208

Dynatrace

OCTOBER 4, 2022

Grail needs to support security data as well as business analytics data and use cases. With that in mind, Grail needs to achieve three main goals with minimal impact to cost: Cope with and manage an enormous amount of data —both on ingest and analytics. High-performance analytics—no indexing required.

Artificial Intelligence 290

Artificial Intelligence Analytics Storage Architecture 290

Dynatrace

OCTOBER 4, 2022

These traditional approaches to log monitoring and log analytics thwart IT teams’ goal to address infrastructure performance problems, security threats, and user experience issues. Data variety is a critical issue in log management and log analytics. The advantage of an index-free system in log analytics and log management.

Analytics 264

Analytics Storage Infrastructure Metrics 264

Dynatrace

MAY 21, 2024

Realizing that executives from other organizations are in a similar situation to my own, I want to outline three key objectives that Dynatrace’s powerful analytics can help you deliver, featuring nine use cases that you might not have thought possible. Change is my only constant. This is inefficient and creates avoidable risks.

Technology 275

Technology Technology Analytics Storage 275

Dynatrace

SEPTEMBER 5, 2024

Customers can also proactively address issues using Davis AI’s predictive analytics capabilities by analyzing network log content, such as retries or anomalies in performance response times. The dashboard tracks a histogram chart of total storage utilized with logs daily. It also tracks the top five log producers by entity.

Innovation 290

Innovation AWS Analytics Storage 290

Dynatrace

OCTOBER 4, 2022

Data warehouses offer a single storage repository for structured data and provide a source of truth for organizations. Unlike data warehouses, however, data is not transformed before landing in storage. A data lakehouse provides a cost-effective storage layer for both structured and unstructured data. Query language.

Artificial Intelligence 246

Artificial Intelligence Storage Analytics Government 246

DZone

FEBRUARY 23, 2023

Any real-time analytics provider or batching/storage adaptor can transform and store data supplied to an event hub. 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.

Azure 306

Azure Big Data Storage Analytics 306

Dynatrace

SEPTEMBER 8, 2022

Log management is an organization’s rules and policies for managing and enabling the creation, transmission, analysis, storage, and other tasks related to IT systems’ and applications’ log data. Comparing log monitoring, log analytics, and log management. It is common to refer to these together as log management and analytics.

Cloud 260

Cloud Systems Analytics DevOps 260

DZone

OCTOBER 24, 2023

The ELK stack is an abbreviation for Elasticsearch, Logstash, and Kibana, which offers the following capabilities: Elasticsearch: a scalable search and analytics engine with a log analytics tool and application-formed database, perfect for data-driven applications.

Analytics 267

Analytics Storage Infrastructure Scalability 267

Scalegrid

FEBRUARY 8, 2024

A distributed storage system is foundational in today’s data-driven landscape, ensuring data spread over multiple servers is reliable, accessible, and manageable. Understanding distributed storage is imperative as data volumes and the need for robust storage solutions rise.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

FEBRUARY 15, 2023

A modern observability and analytics platform brings data silos together and facilitates collaboration and better decision-making among teams. But making decisions about which data to store in easily accessible hot storage upfront requires IT pros to know which questions they want to ask ahead of time and ensure that data is indexed.

Analytics 130

Analytics Storage Cloud DevOps 130

Dynatrace

APRIL 28, 2023

This means compromising between keeping data available as long as possible for analysis while juggling the costs and overhead of storage, archiving, and retrieval. For example, suppose data has to be retained for a longer period because of legal or business reasons.

Analytics 246

Analytics Storage Infrastructure Metrics 246

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.

Big Data 278

Big Data AWS Storage Analytics 278