AWS Big Data

OCTOBER 30, 2023

This framework is ideal for batch analytics workloads from Amazon Simple Storage Service (Amazon S3) and event-based streaming from Amazon Managed Streaming for Apache Kafka (Amazon MSK) and Amazon Kinesis. It was observed that the framework performs well with batch payloads up to 400 MB and streaming data from Amazon MSK and Kinesis.

Cost-Benefit 119

Cost-Benefit Enterprise Data Processing Optimization 119

IBM Big Data Hub

MARCH 21, 2024

Artificial intelligence (AI) is revolutionizing industries by enabling advanced analytics, automation and personalized experiences. Enterprises have reported a 30% productivity gain in application modernization after implementing Gen AI.

Optimization 66

Optimization Software Data-driven Consulting 66

AWS Big Data

JUNE 1, 2023

Amazon Kinesis Data Analytics for Apache Flink is a fully managed service that enables you to use an Apache Flink application to process streaming data. In this blog post, we demonstrate how you can use DJL within Kinesis Data Analytics for Apache Flink for real-time machine learning inference.

Deep Learning 62

Deep Learning Data Analytics Analytics Machine Learning 62

Cloudera

AUGUST 28, 2020

On the B2C side, this means faster download speeds, lower latency and that consumers can download ultra-high-definition video on the go. The real opportunity for 5G however is going to be on the B2B side, IoT and mission-critical applications will benefit hugely. This is the next big opportunity for telcos.

IoT 109

IoT Machine Learning B2B Testing 109

AWS Big Data

MARCH 21, 2024

Your clients that gather the data onsite are written in Python, and they can send all the data as Apache Kafka topics to Amazon MSK. For your application’s low-latency and real-time data access, you can use Lambda and DynamoDB. You can use the same data to train ML models. Create the function.

Data Lake 94

Data Lake Management Modeling Optimization 94

AWS Big Data

JANUARY 9, 2024

Throughout 2023, Amazon OpenSearch Service invested in enabling search teams to use the latest AI/ML technologies to improve and augment your existing search experiences, without having to rewrite your applications or build bespoke orchestrations, resulting in unlocking rapid development, iteration, and productization.

Cost-Benefit 90

Cost-Benefit Visualization Modeling Machine Learning 90

AWS Big Data

DECEMBER 13, 2023

Traditionally, customers used batch-based approaches for data movement from operational systems to analytical systems. A batch-based approach can introduce latency in data movement and reduce the value of data for analytics. usually a data warehouse) needs to reflect those changes in near real-time.

Data Warehouse 96

Data Warehouse Snapshot Data Processing Management 96

IBM Big Data Hub

NOVEMBER 29, 2023

Furthermore, AI algorithms’ capacity for recognizing patterns—by learning from your company’s unique historical data—can empower businesses to predict new trends and spot anomalies sooner and with low latency. Here are some ways that event processing could play a pivotal role in fueling AI capabilities.

Unstructured Data 90

Unstructured Data Data-driven ROI Machine Learning 90

AWS Big Data

MARCH 25, 2024

FMs, as the name suggests, provide the foundation to build more specialized downstream applications, and are unique in their adaptability. Large language models (LLMs) are a type of FM and are pre-trained on vast amounts of text data and typically have application uses such as text generation, intelligent chatbots, or summarization.

Data Lake 88

Data Lake Unstructured Data Management Modeling 88

AWS Big Data

MARCH 7, 2023

This post provides guidance on how to build scalable analytical solutions for gaming industry use cases using Amazon Redshift Serverless. Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning.

Analytics 70

Analytics Data Warehouse Data Lake Metadata 70

IBM Big Data Hub

JULY 5, 2022

Db2’s decades of innovation and expertise running the most demanding transactional, analytical, and operational workloads have culminated today in the 2022 Gartner Peer Insights Customers’ Choice distinction for Cloud Database Management Systems. . No one knows your data like you do. Real-time analytics and ML .

Data Lake 93

Data Lake Data Warehouse Publishing Structured Data 93

IBM Big Data Hub

NOVEMBER 3, 2023

Apache Kafka boasts many strong capabilities, such as delivering a high throughput and maintaining a high fault tolerance in the case of application failure. Apache Kafka streams get data to where it needs to go, but these capabilities are not maximized when Apache Kafka is deployed in isolation.

Cost-Benefit 78

Cost-Benefit Experimentation Testing Digital Transformation 78

Rocket-Powered Data Science

JULY 14, 2023

I recently saw an informal online survey that asked users what types of data (tabular; text; images; or “other”) are being used in their organization’s analytics applications. The results showed that (among those surveyed) approximately 90% of enterprise analytics applications are being built on tabular data.

Analytics 165

Analytics Internet of Things Prescriptive Analytics Data Science 165

IBM Big Data Hub

APRIL 5, 2024

For example, managing the vast volumes of data involved in modern, high-fidelity HPC simulations, modeling and AI model training can be critical, requiring a high-performance storage solution. Regarding GPUs, various industries requiring intensive computing power use them.

Manufacturing 69

Manufacturing Testing Enterprise Modeling 69

AWS Big Data

JANUARY 10, 2024

Thousands of developers use Apache Flink to build streaming applications to transform and analyze data in real time. Apache Flink is an open source framework and engine for processing data streams. Monitoring and scaling your applications is critical to keep your applications running successfully in a production environment.

Metrics 97

Metrics Management Snapshot IT 97

AWS Big Data

APRIL 11, 2023

In this post, we discuss how to streamline inventory management forecasting systems with AWS managed analytics, AI/ML, and database services. With Amazon Athena , retailers can analyze this data to identify trends, patterns, and anomalies, and use Amazon ElastiCache for customer-facing applications with reduced latency.

Forecasting 74

Forecasting Management IoT Data-driven 74

Insight

AUGUST 20, 2019

Spark Spark is one of the most popular tools in distributed computing and can be used for batch and streaming applications. Our Fellows have used Spark in a wide variety of applications from building a platform to discover influencers in GitHub to a real time app for parking spots in Seattle !

Data Warehouse 71

Data Warehouse Big Data Data-driven Data Processing 71

Smart Data Collective

SEPTEMBER 13, 2022

The Android operating system’s official app store allows users to explore and download applications. Following are the benefits of SaaS: 1) Lower Application Costs. Every firm needs lower application costs. SaaS is becoming increasingly popular with business units due to its low initial cost. Examples of SaaS.

Cost-Benefit 102

Cost-Benefit Data Processing Software Data-driven 102

AWS Big Data

APRIL 27, 2023

Amazon OpenSearch Ingestion responds to changing volumes of data, automatically scaling your ingest pipeline. Distributed tracing is the leading way to locate, alert on, and remediate problems with your application and infrastructure. He builds large-scale search applications and solutions.

Strategy 77

Strategy Metrics Data Processing Optimization 77

AWS Big Data

NOVEMBER 16, 2023

In the following sections, we discuss the most common areas of consideration that are critical for Data Vault implementations at scale: data protection, performance and elasticity, analytical functionality, cost and resource management, availability, and scalability. String-optimized compression The Data Vault 2.0

Enterprise 82

Enterprise Data Warehouse Snapshot Cost-Benefit 82

AWS Big Data

JANUARY 17, 2024

Additionally, with version 6.15, Amazon EMR introduces access control protection for its application web interface such as on-cluster Spark History Server, Yarn Timeline Server, and Yarn Resource Manager UI. Select Allow external engines to filter data in Amazon S3 locations registered with Lake Formation.

Data Lake 91

Data Lake Snapshot Big Data Data-driven 91

IBM Big Data Hub

AUGUST 23, 2023

When it comes to hosting applications on Amazon Web Services (AWS), one of the most important decisions you will need to make is which Amazon Elastic Compute Cloud (EC2) instance type to choose. EC2 instances are virtual machines that allow you to run your applications on AWS.

Data Processing 40

Data Processing Optimization Testing Modeling 40

Cloudera

SEPTEMBER 9, 2021

Cloudera Machine Learning or Cloudera Data Warehouse), to deliver fast data and analytics to downstream components. Compared to legacy Apache HBase or Phoenix implementations, COD has been architected to enable organizations optimize infrastructure costs, streamline application development lifecycle and accelerate time to value.

Cost-Benefit 93

Cost-Benefit Optimization Risk Management 93

AWS Big Data

NOVEMBER 17, 2023

Amazon DynamoDB is a fully managed, serverless, key-value NoSQL database designed to run high-performance applications at any scale. DynamoDB offers built-in security, continuous backups, automated multi-Region replication, in-memory caching, and data import and export tools. Under Connection details , choose Create Lambda function.

Visualization 81

Visualization Metadata Testing Internet of Things 81

Rocket-Powered Data Science

JULY 13, 2023

The business challenges then become manifold: talent and technologies now must be harnessed, choreographed, and synchronized to keep up with the data flows that carry and encode essential insights flowing through business processes at light speed. Access to faster analytics addresses that.

Analytics 166

Analytics Machine Learning Deep Learning Data Science 166

Cloudera

FEBRUARY 12, 2019

Changing consumer behaviours and trends are forcing telcos to cater to consumer needs with better data management and analytics, all while keeping a foot in the competition. This puts immense pressure on telcos’ networks to cope with spikes and the larger bandwidth required by data-intensive apps.

IoT 40

IoT Internet of Things Digital Transformation Machine Learning 40

AWS Big Data

FEBRUARY 12, 2024

Objective Gupshup wanted to build a messaging analytics platform that provided: Build a platform to get detailed insights, data, and reports about WhatsApp/SMS campaigns and track the success of every text message sent by the end customers. Incremental analytics is the main reason for Gupshup to use Redshift.

Data Warehouse 98

Data Warehouse Analytics Snapshot Cost-Benefit 98

AWS Big Data

MARCH 27, 2024

Achieving this will also improve general public health through better and more timely interventions, identify health risks through predictive analytics, and accelerate the research and development process. This will be your online transaction processing (OLTP) data store for transactional data.

Data Analytics 89

Data Analytics Analytics Data Warehouse Data Lake 89

AWS Big Data

MARCH 20, 2023

In this post, we share how Poshmark improved CX and accelerated revenue growth by using a real-time analytics solution. High-level challenge: The need for real-time analytics Previous efforts at Poshmark for improving CX through analytics were based on batch processing of analytics data and using it on a daily basis to improve CX.

Analytics 52

Analytics Slice and Dice Data Processing Data Lake 52

AWS Big Data

FEBRUARY 21, 2024

Integrating streaming data into Amazon Redshift brings immense value by enabling organizations to harness the potential of real-time analytics and data-driven decision-making. This solution is also applicable for customers that are looking to use Amazon MSK Serverless and Amazon Redshift Serverless.

Analytics 105

Analytics Management Data-driven Data Integration 105

AWS Big Data

MARCH 28, 2024

To optimize the reconciliation process, these users require high performance transformation with the ability to scale on demand, as well as the ability to process variable file sizes ranging from as low as a few MBs to more than 100 GB. We define our SLA in two dimensions: latency and throughput.

Optimization 79

Optimization IT Big Data Data Processing 79

AWS Big Data

JUNE 13, 2023

This post presents a reference architecture for real-time queries and decision-making on AWS using Amazon Kinesis Data Analytics for Apache Flink. In addition, we explain why the Klarna Decision Tooling team selected Kinesis Data Analytics for Apache Flink for their first real-time decision query service.

Data Analytics 52

Data Analytics Analytics Risk Snapshot 52

AWS Big Data

OCTOBER 4, 2023

Amazon EMR with Spot Instances allows you to reduce costs for running your big data workloads on AWS. Spot Instances are best suited for running stateless and fault-tolerant big data applications such as Apache Spark with Amazon EMR, which are resilient against Spot node interruptions. Create an EMR 6.9.0

Big Data 79

Big Data Optimization Data-driven Management 79

AWS Big Data

JANUARY 31, 2024

This post is cowritten with Pramod Nayak, LakshmiKanth Mannem and Vivek Aggarwal from the Low Latency Group of LSEG. Capturing every single message is critical for transaction cost analytics, market liquidity monitoring, trading strategy evaluation, and market research. In the Analytics engine section, select Apache Spark.

Marketing 82

Marketing Analytics Visualization Strategy 82

AWS Big Data

JUNE 21, 2023

OpenSearch is a scalable, flexible, and extensible open-source software suite for search, analytics, security monitoring, and observability applications, licensed under the Apache 2.0 The following diagram shows an example architecture for a semantic search application with OpenSearch Service as the vector database.

Metrics 77

Metrics Measurement Modeling Dashboards 77

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Data is part of the applications running within that very large server.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

MAY 16, 2023

In today’s digital age, logging is a critical aspect of application development and management, but efficiently managing logs while complying with data protection regulations can be a significant challenge. The exact length of time required for data storage varies depending on the specific regulation and the type of data being stored.

Data Lake 68

Data Lake Cost-Benefit Optimization Testing 68