Cloudera

AUGUST 26, 2021

In addition to big data workloads, Ozone is also fully integrated with authorization and data governance providers namely Apache Ranger & Apache Atlas in the CDP stack. While we walk through the steps one by one from data ingestion to analysis, we will also demonstrate how Ozone can serve as an ‘S3’ compatible object store.

Data Science 109

Data Science Cloud Hadoop Metadata 109

Rockset

JANUARY 30, 2024

Microbatching : An option to microbatch ingestion based on the latency requirements of the use case. In this blog, we delve into each of these features and how they are giving users more cost controls for their search and AI applications. This is not a hands-free operation and also involves the transfer of data across nodes.

Data Ingestion 64

Data Ingestion Utilities Architecture SQL 64

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Ensuring Data Quality in New Data Sources (#1) Introduction to Data Evaluation in Data Observability Ensuring their quality and integrity before incorporating new data sources into production is paramount. When looking at new data, does one patch the data?

Data Cleanse 51

Data Cleanse Data Ingestion Data Datasets 51

ProjectPro

FEBRUARY 6, 2023

With over 10 million active subscriptions, 50 million active topics, and a trillion messages processed per day, Google Cloud Pub/Sub makes it easy to build and manage complex event-driven systems. Google Cloud Pub/Sub is a global, cloud-based messaging framework that has become increasingly popular among data engineers over recent years.

Google Cloud 52

Google Cloud Cloud Cloud Storage Data Ingestion 52

Data Engineering Weekly

OCTOBER 30, 2022

Luis Velasco: Data Contracts - The Mesh Glue I'm excited about the Schemata & Data contract because it perfectly stitches catalogs, data quality, and glossary. The current state of these systems is inherently passive systems. The author explains how to dump the history of blockchains into S3.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Ingestion 52

Cloudera

DECEMBER 14, 2021

But with growing demands, there’s a more nuanced need for enterprise-scale machine learning solutions and better data management systems. The 2021 Data Impact Awards aim to honor organizations who have shown exemplary work in this area. . For this, the RTA transformed its data ingestion and management processes. .

Transportation 107

Transportation Telecommunication Banking Data Lake 107

Databand.ai

JULY 17, 2023

The main components of MLOps include: Data management: Ensuring data quality and consistency throughout the entire ML lifecycle. Model training: Developing robust training pipelines with version control systems for reproducibility.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

Data Engineering Weekly

MARCH 5, 2023

The basics of the best practices are to establish Meta’s Ground Truth Maturity Framework [GTMF] [link] Google: Datasets at your fingertips in Google Search Easy access to the datasets is 80% of the problem solved in data engineering. link] The blog highlights six key principles of the value creation of data.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

DataKitchen

OCTOBER 2, 2023

Data Teams and Their Types of Data Journeys In the rapidly evolving landscape of data management and analytics, data teams face various challenges ranging from data ingestion to end-to-end observability. It explores why DataKitchen’s ‘Data Journeys’ capability can solve these challenges.

Data Ingestion 40

Data Ingestion Data Government Datasets 40

Knowledge Hut

MARCH 19, 2024

I will explore the top 10 AWS applications and their use cases in this blog. Amazon Redshift Amazon Redshift is a completely managed data warehousing service that enables organizations to analyze large datasets with standard SQL queries. What is AWS? Conclusion AWS has released over two hundred production-level services.

AWS 52

AWS Cloud Computing Amazon Web Services Relational Database 52

Cloudera

JANUARY 20, 2021

The missing chapter is not about point solutions or the maturity journey of use cases, the missing chapter is about the data, it’s always been about the data, and most importantly the journey data weaves from edge to artificial intelligence insight. . Conclusion.

Manufacturing 105

Manufacturing Data Warehouse Kafka Retail 105

Cloudera

NOVEMBER 17, 2020

Knowing that a transaction is fraudulent is a critical requirement for financial services companies, but knowing that a transaction that was flagged by a rules-based system as fraudulent is a valid transaction, can be equally important. Data analysis – create a plan to build the model.

Deep Learning 110

Deep Learning Machine Learning Raw Data Data Ingestion 110

Monte Carlo

MARCH 24, 2023

Besides the zoo example, some other examples of data integrity include ensuring that data is not accidentally or maliciously altered, preventing unauthorized access to sensitive information, and maintaining the consistency of data across multiple databases or systems. How Do You Maintain Data Integrity?

Data Validation 52

Data Validation Data Integration Data Cleanse Data Pipeline 52

Rockset

DECEMBER 27, 2022

That said, under the hood Elasticsearch is a complex, distributed system with many levers to pull to achieve optimal performance. In this blog, we walk through solutions to common Elasticsearch performance challenges at scale including slow indexing, search speed, shard and index sizing, and multi-tenancy.

Data Ingestion 52

Data Ingestion NoSQL Datasets Utilities 52

phData: Data Engineering

SEPTEMBER 19, 2023

With many data modeling methodologies and processes available, choosing the right approach can be daunting. This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

LinkedIn Engineering

DECEMBER 12, 2023

We say that an algorithm is differentially private if any result of the algorithm cannot depend too much on any single data record in a dataset. Hence, differential privacy provides uncertainty for whether or not an individual data record is in the dataset.

Algorithm 77

Algorithm Metadata SQL Datasets 77

Rockset

JANUARY 26, 2023

The goal of this blog post is to provide best practices on how to use terraform to configure Rockset to ingest the data into two collections, and how to setup a view and query lambdas that are used in an application, plus to show the workflow of later updating the query lambdas.

AWS 52

AWS SQL Datasets Kafka 52

Confluent

FEBRUARY 6, 2019

The blog posts How to Build and Deploy Scalable Machine Learning in Production with Apache Kafka and Using Apache Kafka to Drive Cutting-Edge Machine Learning describe the benefits of leveraging the Apache Kafka ® ecosystem as a central, scalable and mission-critical nervous system. You need to think about the whole model lifecycle.

Machine Learning 107

Machine Learning Python Kafka Java 107

Rockset

MAY 17, 2022

This is the fourth post in a series by Rockset's CTO Dhruba Borthakur on Designing the Next Generation of Data Systems for Real-Time Analytics. We'll be publishing more posts in the series in the near future, so subscribe to our blog so you don't miss them!

SQL 52

SQL NoSQL Hadoop MongoDB 52

Netflix Tech

OCTOBER 19, 2020

which is difficult when troubleshooting distributed systems. In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. Troubleshooting a session in Edgar When we started building Edgar four years ago, there were very few open-source distributed tracing systems that satisfied our needs.

Building 93

Building Transportation Metadata Java 93

DareData

JULY 5, 2023

In this blog post, we aim to share practical insights and techniques based on our real-world experience in developing data lake infrastructures for our clients - let's start! Typically, it is advisable to retain the data in its original, unaltered format when transferring it from any source to the data lake layer.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

ProjectPro

JANUARY 19, 2022

Source: Image uploaded by Tawfik Borgi on (researchgate.net) So, what is the first step towards leveraging data? The first step is to work on cleaning it and eliminating the unwanted information in the dataset so that data analysts and data scientists can use it for analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

ProjectPro

FEBRUARY 21, 2023

With so many data engineering certifications available , choosing the right one can be a daunting task. There are over 133K data engineer job openings in the US, but how will you stand out in such a crowded job market? Why Are Data Engineering Skills In Demand? Don’t worry!

Certification 52

Certification Data Engineering Data Engineer Engineering 52

ProjectPro

DECEMBER 7, 2021

Data pipelines are a significant part of the big data domain, and every professional working or willing to work in this field must have extensive knowledge of them. Data Pipeline Tools AWS Data Pipeline Azure Data Pipeline Airflow Data Pipeline Learn to Create a Data Pipeline FAQs on Data Pipeline What is a Data Pipeline?

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Cloudera

JULY 18, 2018

The joint solution provides the following core capabilities: Automated natural language processing (NLP) of unstructured clinical notes, in order to store as structured, reportable data that can be rapidly searched and analyzed intelligently. Real-time and batch processing from any EHR system including multi-year historical loads.

Machine Learning 50

Machine Learning Healthcare Medical Electronics 50

ProjectPro

FEBRUARY 16, 2023

From monitoring and searching through big data to generating alerts, reports, and visualizations, Splunk offers several such features to help businesses achieve their goals. This clearly shows how crucial it is for data engineers to be familiar with the Splunk platform if they want to succeed in the big data industry.

Big Data 52

Big Data Big Data Tools Cloud Data 52

Knowledge Hut

APRIL 25, 2023

An end-to-end Data Science pipeline starts from business discussion to delivering the product to the customers. One of the key components of this pipeline is Data ingestion. It helps in integrating data from multiple sources such as IoT, SaaS, on-premises, etc., What is Data Ingestion?

Data Ingestion 52

Data Ingestion Lambda Architecture Raw Data Kafka 52

Rockset

MAY 3, 2023

lower latency than Elasticsearch for streaming data ingestion. In this blog, we’ll walk through the benchmark framework, configuration and results. We’ll also delve under the hood of the two databases to better understand why their performance differs when it comes to search and analytics on high-velocity data streams.

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

Cloudera

SEPTEMBER 17, 2018

Here are some highlights: Data Ingest. Most data is ingested through data engineering pipelines. Once you found your datasets of interest, there are easy ways to tag them, so that you at next visit can find them immediately – the search functionality also covers tags!

Data Warehouse 52

Data Warehouse SQL Portfolio MySQL 52

Rockset

MARCH 1, 2023

When you deconstruct the core database architecture, deep in the heart of it you will find a single component that is performing two distinct competing functions: real-time data ingestion and query serving. When data ingestion has a flash flood moment, your queries will slow down or time out making your application flaky.

Data Ingestion 144

Data Ingestion Database Architecture Cloud Storage 144

Snowflake

APRIL 18, 2024

This blog post explores how Snowflake can help with this challenge. Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention. Security teams can also reduce their costs by loading certain datasets in batches instead of continuously.

Data Lake 78

Data Lake Data Ingestion Bytes Cloud Computing 78

Pinterest Engineering

SEPTEMBER 12, 2023

transformers) became standardized, ML engineers started to show a growing appetite to iterate on datasets. While such dataset iterations can yield significant gains, we observed that only a handful of such experiments were conducted and productionized in the last six months. As model architecture building blocks (e.g.

Data Process 88

Data Process Process Datasets Scala 88

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. ® , Go, and Python SDKs where an application can use SQL to query raw data coming from Kafka through an API (but that is a topic for another blog). Joining with other datasets.

Kafka 21

Kafka BI SQL Datasets 21

Cloudera

SEPTEMBER 7, 2023

Institutions must design AI systems that are not only transparent, reliable, fair, and accountable, but also comply with privacy and security requirements, as well as align with human values and norms. It’s the most revolutionary technological development in at least a generation. But it’s also fraught with risk.

Insurance 79

Insurance Finance Portfolio Government 79

Data Engineering Weekly

NOVEMBER 20, 2022

Google AI: The Data Cards Playbook: A Toolkit for Transparency in Dataset Documentation Google published Data Cards , a dataset documentation framework aimed at increasing transparency across dataset lifecycles. link] The short YouTube video gives a nice overview of the Data Cards.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

ProjectPro

AUGUST 24, 2021

Data professionals who work with raw data like data engineers, data analysts, machine learning scientists , and machine learning engineers also play a crucial role in any data science project. And, out of these professions, this blog will discuss the data engineering job role.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Ascend.io

JUNE 6, 2023

In this blog post, we delve deep into the factors that contribute to how Ascend runs in the cloud, focusing on the primary areas that contribute to costs in this context: storage, compute, networking, and retries. To get to the bottom of actual infrastructure costs, this reference system uses open-source Spark. cents per gigabyte.

Cloud 52

Cloud Data Pipeline Data Ingestion Cloud Storage 52