Cloudera

AUGUST 4, 2021

In fact, McKinsey points to a 50% reduction in downtime and a 40% reduction in maintenance costs when using IoT and data analytics to predict and prevent breakdowns. Navistar relies on predictive maintenance, which leverages IoT and data analytics to predict and prevent breakdowns of commercial trucks and school buses. “We

Unstructured Data 98

Unstructured Data Data Ingestion Government Machine Learning 98

Cloudera

FEBRUARY 8, 2021

Future connected vehicles will rely upon a complete data lifecycle approach to implement enterprise-level advanced analytics and machine learning enabling these advanced use cases that will ultimately lead to fully autonomous drive.

Manufacturing 108

Manufacturing Machine Learning Data Ingestion Electronics 108

Snowflake

MARCH 14, 2024

Customers can process changed data once or twice a day — or at whatever cadence they prefer — to the main table. SNP has been able to provide customers with a 10x cost reduction in Snowflake data processing associated with SAP data ingestion.

IT 121

IT Data Ingestion Data AWS 121

Snowflake

APRIL 18, 2024

Legacy SIEM cost factors to keep in mind Data ingestion: Traditional SIEMs often impose limits to data ingestion and data retention. Snowflake allows security teams to store all their data in a single platform and maintain it all in a readily accessible state, with virtually unlimited cloud data storage capacity.

Data Lake 108

Data Lake Data Ingestion Bytes Cloud Computing 108

Data Engineering Podcast

OCTOBER 12, 2020

Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud. Learn how we streamline and accelerate manual processes to help you derive real results from your data at dataengineeringpodcast.com/immuta.

Business Intelligence 100

Business Intelligence BI Consulting Data Ingestion 100

Cloudera

OCTOBER 13, 2021

What’s data analytics and why is everyone talking about it?”. Read the book to find out what they mean, and why NiFi is an essential tool for data ingestion and movement. Don’t know what data ingestion is? Using these books, you can answer questions such as: . Already confused by unfamiliar words?

Machine Learning 75

Machine Learning Data Ingestion Algorithm Technology 75

Data Engineering Podcast

NOVEMBER 16, 2020

At Isima they decided to reimagine the entire ecosystem from the ground up and built a single unified platform to allow end-to-end self service workflows from data ingestion through to analysis. Immuta is an automated data governance solution that enables safe and easy data analytics in the cloud.

Data Management 100

Data Management Management BI Business Intelligence 100

Rockset

JULY 29, 2022

The Snowpipe feature manages continuous data ingestion. However, this continuous streaming data isn’t available for a few minutes. This delay makes it unappealing for real-time analytics because you can’t query data immediately. This is true for the three data warehouses mentioned above.

Data Analytics 52

Data Analytics Data Warehouse Datasets Cloud 52

Striim

SEPTEMBER 11, 2024

Data Collection/Ingestion The next component in the data pipeline is the ingestion layer, which is responsible for collecting and bringing data into the pipeline. By efficiently handling data ingestion, this component sets the stage for effective data processing and analysis.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

Towards Data Science

DECEMBER 1, 2023

Pet Project for Data/Analytics Engineers: Explore Modern Data Stack Tools — dbt Core, Snowflake, Fivetran, GitHub Actions. This hands-on experience will allow you to develop an end-to-end data lifecycle, from extracting data from your Google Calendar to presenting it in a Snowflake analytics dashboard.

Data Engineering 97

Data Engineering Data Engineer Project Engineering 97

Confluent

FEBRUARY 6, 2019

It allows real-time data ingestion, processing, model deployment and monitoring in a reliable and scalable way. This blog post focuses on how the Kafka ecosystem can help solve the impedance mismatch between data scientists, data engineers and production engineers. Kai Waehner works as technology evangelist at Confluent.

Machine Learning 107

Machine Learning Python Kafka Java 107

Cloudera

APRIL 22, 2021

Today’s enterprise data analytics teams are constantly looking to get the best out of their platforms. Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it.

Pipeline-centric 101

Pipeline-centric Data Lake Hadoop Big Data 101

Data Engineering Podcast

OCTOBER 30, 2022

Summary One of the most impactful technologies for data analytics in recent years has been dbt. It’s hard to have a conversation about data engineering or analysis without mentioning it. Despite its widespread adoption there are still rough edges in its workflow that cause friction for data analysts.

Engineering 100

Engineering MongoDB MySQL Scala 100

Christophe Blefari

JANUARY 20, 2024

The main difference between both is the fact that your computation resides in your warehouse with SQL rather than outside with a programming language loading data in memory. In this category I recommend also to have a look at data ingestion (Airbyte, Fivetran, etc.), workflows (Airflow, Prefect, Dagster, etc.)

Data Engineering 130

Data Engineering Data Engineer Engineering Hadoop 130

Cloudera

MAY 30, 2024

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission-critical, large-scale data analytics and AI use cases—including enterprise data warehouses.

Data Lake 74

Data Lake Data Warehouse Programming Language Data Ingestion 74

Snowflake

NOVEMBER 29, 2023

While the former can be solved by tokenization strategies provided by external vendors, the latter mandates the need for patient-level data enrichment to be performed with sufficient guardrails to protect patient privacy, with an emphasis on auditability and lineage tracking.

Metadata 114

Metadata Healthcare Medical Data Storage 114

Cloudera

SEPTEMBER 28, 2020

The customer leverages Cloudera’s multi-function analytics stack in CDP. The data lifecycle model ingests data using Kafka, enriches that data with Spark-based batch process, performs deep data analytics using Hive and Impala, and finally uses that data for data science using Cloudera Data Science Workbench to get deep insights.

Cloud 132

Cloud Kafka Professional Services Metadata 132

Databand.ai

AUGUST 30, 2023

DataOps , short for data operations, is an emerging discipline that focuses on improving the collaboration, integration, and automation of data processes across an organization. These tools help organizations implement DataOps practices by providing a unified platform for data teams to collaborate, share, and manage their data assets.

Data Cleanse 52

Data Cleanse Data Pipeline Data Ingestion Data Validation 52

Cloudera

APRIL 13, 2021

CDP addresses the high multi-tenancy, contention isolation, and workload demands of the company’s largest customer use cases—all while enabling the company to find and implement unique data analytics products and services. Its existing data architecture, however, wasn’t up for the gig.

Cloud 78

Cloud Pharmaceutical Data Warehouse Medical 78

Cloudera

FEBRUARY 16, 2021

In the following sections, we see how the Cloudera Operational Database is integrated with other services within CDP that provide unified governance and security, data ingest capabilities, and expand compatibility with Cloudera Runtime components to cater to your specific use cases. . Integrated across the Enterprise Data Lifecycle .

Database 83

Database Machine Learning Kafka Aggregated Data 83

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Cloudera

JULY 21, 2022

This is especially useful when the data in Druid needs to be joined with the data residing elsewhere in the warehouse. The table below summarizes Hive and Druid key features and strengths and suggests how combining the feature sets can provide the best of both worlds for data analytics. Cloudera Data Warehouse).

BI 87

BI Digital Media Data Warehouse Kafka 87

Edureka

AUGUST 23, 2024

Introduction Data analytics is imperative for business success. AI-driven data insights make it possible to improve decision-making. These analytic models can work on processed data sets. The accuracy of decisions improves dramatically once you can use live data in real-time. How Amazon Kinesis Works?

AWS 52

AWS Kafka Amazon Web Services Medical 52

Data Engineering Weekly

APRIL 21, 2024

link] RevenueCat: How we solved RevenueCat’s biggest challenges on data ingestion into Snowflake A common design feature of modern data lakes and warehouses is that Inserts and deletes are fast, but the cost of scattered updates grows linearly with the table size.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

LinkedIn Engineering

DECEMBER 12, 2023

Hence, we want to safeguard the privacy of members when they view posts while also providing useful analytics of viewers on their own posts. We will start with a general overview of differential privacy, the gold standard of enforcing privacy for data analytics, which we adopt in post analytics.

Algorithm 77

Algorithm Metadata SQL Utilities 77

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs.

Raw Data 50

Raw Data Data Ingestion Datasets Data 50

Confluent

SEPTEMBER 26, 2019

In the early days, many companies simply used Apache Kafka ® for data ingestion into Hadoop or another data lake. Kai’s main area of expertise lies within the fields of big data analytics, machine learning, integration, microservices, Internet of Things, stream processing, and blockchain.

Kafka 21

Kafka SQL BI Hadoop 21

Cloudera

JUNE 16, 2022

Faster data ingestion: streaming ingestion pipelines. Building real-time data analytics pipelines is a complex problem, and we saw customers struggle using processing frameworks such as Apache Storm, Spark Streaming, and Kafka Streams. .

Kafka 88

Kafka Manufacturing Data Lake SQL 88

ProjectPro

AUGUST 24, 2021

So, working on a data warehousing project that helps you understand the building blocks of a data warehouse is likely to bring you more clarity and enhance your productivity as a data engineer. Data Analytics: A data engineer works with different teams who will leverage that data for business solutions.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

Knowledge Hut

JUNE 26, 2023

Here are some data engineering project ideas to consider and Data Engineering portfolio project examples to demonstrate practical experience with data engineering problems. Realtime Data Analytics Project Overview: Olber, a corporation that provides taxi services, is gathering information about each and every journey.

Data Engineering 98

Data Engineering Data Engineer Coding Project 98

Data Engineering Weekly

MARCH 17, 2024

Vague Definitions and Overreach Misplaced Focus on Policy and Compliance Inadequate Understanding of Data Quality and Representation I agree with these comments; we need to better define data governance in alignment with the emerging AI standards. The article compares all the VectorDB available in the market.

Data Engineering 71

Data Engineering Data Engineer Engineering Kafka 71

Knowledge Hut

NOVEMBER 2, 2023

An Azure Data Engineer is a professional who is in charge of designing, implementing, and maintaining data processing systems and solutions on the Microsoft Azure cloud platform. A Data Engineer is responsible for designing the entire architecture of the data flow while taking the needs of the business into account.

Data Engineering 52

Data Engineering Data Engineer Project Coding 52

Rockset

MARCH 5, 2021

Extending this analogy to the world of data analytics: “time” is query latency and “energy” is compute cost. Continuous Data Ingestion in Minutes vs. Milliseconds Snowpipe is Snowflake’s continuous data ingestion service. Using the index will save you a LOT of time and energy.

Cloud Storage 52

Cloud Storage Data Ingestion Data Warehouse Computer Science 52

Cloudyard

JULY 16, 2024

The Snowflake Solution: The Snowflake Solution: This pipeline utilizes a series of tasks and tables to achieve real-time data ingestion and historical tracking : Source Table (CUSTOMER_SRC): This temporary staging area holds the latest customer data received from your external system.

Data Ingestion 52

Data Ingestion Data Pipeline Metadata Utilities 52

Knowledge Hut

SEPTEMBER 26, 2023

Organisations are constantly looking for robust and effective platforms to manage and derive value from their data in the constantly changing landscape of data analytics and processing. These platforms provide strong capabilities for data processing, storage, and analytics, enabling companies to fully use their data assets.

Data Lake 52

Data Lake Database-centric Machine Learning Pipeline-centric 52

Snowflake

MARCH 13, 2023

What started as a venture by three seasoned cybersecurity and cloud professionals—with support from venture group Team8—now offers an end-to-end infrastructure security solution combining data analytics with domain-specific cybersecurity expertise. Konigsberg added: “Data ingestion is a notoriously time-consuming and costly exercise.

Cloud 52

Cloud Building Data Ingestion AWS 52

Confluent

OCTOBER 10, 2019

MQTT Proxy for data ingestion without an MQTT broker. In some scenarios, the main challenge and requirement is to ingest data into Kafka for further processing and analytics in other backend systems. Download the Confluent Platform to get started with the leading distribution of Apache Kafka.

Kafka 20

Kafka Google Cloud Architecture Machine Learning 20