DataKitchen

MAY 10, 2024

And how can a data engineer give their provider a ‘score’ on the data based on fact? The First of Five Use Cases in Data Observability Data Evaluation: This involves evaluating and cleansing new datasets before being added to production. This process is critical as it ensures data quality from the onset.

Data Cleanse 49

Data Cleanse Data Ingestion Data Datasets 49

ProjectPro

JANUARY 19, 2022

Data Engineering is gradually becoming a popular career option for young enthusiasts. Explore this page further and learn everything about data engineers to find the answer. We will cover it all, from its definition, skills, responsibilities to the significance of data engineer in an institution.

Data Engineering 52

Data Engineering Data Engineer Engineering Amazon Web Services 52

Databand.ai

JULY 17, 2023

By adopting a set of best practices inspired by Agile methodologies, DevOps principles, and statistical process control techniques, DataOps helps organizations deliver high-quality data insights more efficiently. The main components of MLOps include: Data management: Ensuring data quality and consistency throughout the entire ML lifecycle.

Data Pipeline 52

Data Pipeline Machine Learning High Quality Data BI 52

ProjectPro

FEBRUARY 6, 2023

Google Cloud Pub/Sub is a global, cloud-based messaging framework that has become increasingly popular among data engineers over recent years. Data engineers often use Google Cloud Pub/Sub to design asynchronous workflows, publish event notifications, and stream data from several processes or devices.

Google Cloud 52

Google Cloud Cloud Cloud Storage Data Ingestion 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. . STEP 5: Push data to storage solutions. Conclusion.

Manufacturing 105

Manufacturing Data Warehouse Kafka Retail 105

Cloudera

APRIL 9, 2021

This is part 4 in this blog series. This blog series follows the manufacturing and operations data lifecycle stages of an electric car manufacturer – typically experienced in large, data-driven manufacturing companies. The second blog dealt with creating and managing Data Enrichment pipelines.

Machine Learning 98

Machine Learning Manufacturing Data Collection Data Science 98

Cloudera

FEBRUARY 16, 2021

In the previous blog post , we looked at some of the application development concepts for the Cloudera Operational Database (COD). In this blog post, we’ll see how you can use other CDP services with COD. Integrated across the Enterprise Data Lifecycle . Cloudera Data Engineering to ingest bulk data and data from mainframes.

Database 81

Database Machine Learning Data Lake Kafka 81

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

Monte Carlo

MARCH 24, 2023

We often refer to these issues as data freshness or stale data. For example: The source system could provide corrupt data or rows with excessive NULLs. A poorly coded data pipeline could introduce an error during the data ingestion phase as the data is being clean or normalized. What Is Data Validity?

Data Validation 52

Data Validation Data Integration Data Cleanse Data Pipeline 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. For now, we’ll focus on Kafka.

Machine Learning 107

Machine Learning Python Kafka Java 107

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

DECEMBER 27, 2022

Scaling Elasticsearch Elasticsearch is a NoSQL search and analytics engine that is easy to get started using for log analytics, text search, real-time analytics and more. Many solutions originate from interviews and discussions with engineering leaders and architects who have hands-on experience operating the system at scale.

Data Ingestion 52

Data Ingestion NoSQL Datasets Utilities 52

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! Instant scaleup of data writes or queries to handle bursts of data.

SQL 52

SQL NoSQL Hadoop MongoDB 52

phData: Data Engineering

SEPTEMBER 19, 2023

By employing robust data modeling techniques, businesses can unlock the true value of their data lake and transform it into a strategic asset. With many data modeling methodologies and processes available, choosing the right approach can be daunting. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Netflix Tech

OCTOBER 19, 2020

a Netflix member via Twitter This is an example of a question our on-call engineers need to answer to help resolve a member issue?—?which In our previous blog post we introduced Edgar, our troubleshooting tool for streaming sessions. We needed to increase engineering productivity via distributed request tracing.

Building 93

Building Transportation Metadata Java 93

RandomTrees

SEPTEMBER 6, 2020

Lot of cloud-based data warehouses are available in the market today, out of which let us focus on Snowflake. Snowflake is an analytical data warehouse that is provided as Software-as-a-Service (SaaS). Built on new SQL database engine, it provides a unique architecture designed for the cloud.

Cloud Storage 52

Cloud Storage Data Ingestion Data Cleanse Data Warehouse 52

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

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. A pipeline may include filtering, normalizing, and data consolidation to provide desired data. ETL is the acronym for Extract, Transform, and Load.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

LinkedIn Engineering

JUNE 15, 2023

To remove this bottleneck, we built AvroTensorDataset , a TensorFlow dataset for reading, parsing, and processing Avro data. AvroTensorDataset speeds up data preprocessing by multiple orders of magnitude, enabling us to keep site content as fresh as possible for our members. avro", "part-00001.avro"], Default is zero.

Datasets 102

Datasets Bytes Process Data Ingestion 102

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

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! Visualization.

Data Warehouse 52

Data Warehouse SQL Portfolio MySQL 52

Rockset

JULY 19, 2021

However, using Druid can be problematic when used outside its normal parameters — for example, to work with nested data. In this article, we’ll discuss ingesting and using nested data in Apache Druid. Druid doesn’t store nested data in the form often found in, say, a JSON dataset.

Programming Language 40

Programming Language Data Ingestion Data Database 40

Data Engineering Weekly

NOVEMBER 20, 2022

Data Engineering Weekly Is Brought to You by RudderStack RudderStack provides data pipelines that make it easy to collect data from every application, website, and SaaS platform, then activate it in your warehouse and business tools. link] The short YouTube video gives a nice overview of the Data Cards.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Pinterest Engineering

SEPTEMBER 12, 2023

Raymond Lee | Software Engineer II; Qingxian Lai | Sr. Software Engineer; Karthik Anantha Padmanabhan | Manager II, Engineering; Se Won Jang | Manager II, Engineering Photo by Claudio Schwarz on Unsplash Our mission at Pinterest is to bring everyone the inspiration to create the life they love.

Data Process 88

Data Process Process Datasets Scala 88

Rockset

MAY 3, 2023

In scenarios involving analytics on massive data streams, we’re often asked the maximum throughput and lowest data latency Rockset can achieve and how it stacks up to other databases. For this benchmark, we evaluated Rockset and Elasticsearch ingestion performance on throughput and data latency. How did we do it?:

Data Ingestion 59

Data Ingestion Kafka Database Architecture 59

ProjectPro

AUGUST 24, 2021

Nevertheless, that is not the only job in the data world. 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.

Data Engineering 52

Data Engineering Data Engineer Coding Project 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

Cloudera

MAY 19, 2021

In the previous blog post in this series, we walked through the steps for leveraging Deep Learning in your Cloudera Machine Learning (CML) projects. RAPIDS brings the power of GPU compute to standard Data Science operations, be it exploratory data analysis, feature engineering or model building. Get the Dataset.

Machine Learning 136

Machine Learning Datasets Data Science Raw Data 136

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). However, Apache Kafka is more than just messaging.

Kafka 21

Kafka BI SQL Datasets 21

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. This allows for data ingestion from sources outside the subnet, and access for authenticated users.

Cloud 52

Cloud Data Pipeline Data Ingestion Cloud Storage 52

Ascend.io

JUNE 8, 2023

However, transforming data into a product so that it can deliver outsized business value requires more than just a mission statement; it requires a solid foundation of technical capabilities and a truly data-centric culture. This multitude of sources often causes a dispersed, complex, and poorly structured data landscape.

Pipeline-centric 52

Pipeline-centric Database-centric Data Ingestion Data Pipeline 52

Cloudera

FEBRUARY 8, 2021

This is part 2 in this blog series. You can read part 1, here: Digital Transformation is a Data Journey From Edge to Insight. The first blog introduced a mock connected vehicle manufacturing company, The Electric Car Company (ECC), to illustrate the manufacturing data path through the data lifecycle.

Data Pipeline 114

Data Pipeline Building Manufacturing Data Warehouse 114

phData: Data Engineering

FEBRUARY 16, 2023

This is due to a number of reasons, which we covered in a previous blog post , but in short, it’s primarily due to a need to accelerate platform adoption outside of central IT teams. When used with the Snowflake Data Cloud , dbt Cloud is the perfect match for our customers looking to scale and grow platform adoption.

Cloud 52

Cloud Database Data Ingestion Coding 52

Cloudera

SEPTEMBER 9, 2022

analyst Sumit Pal, in “Exploring Lakehouse Architecture and Use Cases,” published January 11, 2022: “Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support AI, BI, ML, and data engineering on a single platform.” According to Gartner, Inc.

Architecture 97

Architecture Metadata Unstructured Data Machine Learning 97

ProjectPro

JANUARY 25, 2022

Here’s What You Need to Know About PySpark This blog will take you through the basics of PySpark, the PySpark architecture, and a few popular PySpark libraries , among other things. Finally, you'll find a list of PySpark projects to help you gain hands-on experience and land an ideal job in Data Science or Big Data.

Big Data 52

Big Data Data Process Process Kafka 52