Cloudera

DECEMBER 15, 2022

Today, we are thrilled to share some new advancements in Cloudera’s integration of Apache Iceberg in CDP to help accelerate your multi-cloud open data lakehouse implementation. Multi-cloud deployment with CDP public cloud. Multi-cloud capability is now available for Apache Iceberg in CDP. Advanced capabilitie.

Cloud 78

Cloud Metadata Google Cloud Data Warehouse 78

Cloudera

APRIL 21, 2021

You can learn more about how we moved to CDP [ADD WEBINAR DETAILS]. The most important step in a successful upgrade to CDP Private Cloud Base is understanding your environment. Despite these challenges, we knew we wanted to go to CDP Private Cloud. In this blog, we discuss our journey to CDP for this critical cluster.

Cloud 121

Cloud Professional Services Java Data Warehouse 121

Data Engineering Podcast

MAY 11, 2020

His most recent endeavor at StreamNative is focused on combining the capabilities of Pulsar with the cloud native movement to make it easier to build and scale real time messaging systems with built in event processing capabilities. Tidy Data is the DataOps monitoring platform that you’ve been missing.

Cloud 100

Cloud Lambda Architecture Kafka Hadoop 100

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 93

Data Lake Data Warehouse BI SQL 93

Precisely

MARCH 10, 2023

With the right geocoding technology, accurate and standardized address data is entirely possible. This capability opens the door to a wide array of data analytics applications. The Rise of Cloud Analytics Data analytics has advanced rapidly over the past decade. That effort led to a dramatic shift toward the cloud.

Datasets 59

Datasets Data Warehouse Big Data Data Analytics 59

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Deploying modern data architectures. Forrester ).

Data Architecture 78

Data Architecture Architecture Data Lake NoSQL 78

Snowflake

APRIL 9, 2024

For a more in-depth exploration, plus advice from Snowflake’s Travis Henry, Director of Sales Development Ops and Enablement, and Ryan Huang, Senior Marketing Data Analyst, register for our Snowflake on Snowflake webinar on boosting market efficiency by leveraging data from Outreach. But that’s not all.

BI 79

BI Data Ingestion Data Aggregated Data 79

Data Engineering Podcast

OCTOBER 9, 2018

Summary One of the most complex aspects of managing data for analytical workloads is moving it from a transactional database into the data warehouse. The Skafos platform from Metis Machine was built to give your data scientists the end-to-end support that they need throughout the machine learning lifecycle.

PostgreSQL 100

PostgreSQL BI Machine Learning Data Warehouse 100

Cloudera

OCTOBER 29, 2020

With the massive explosion of data across the enterprise — both structured and unstructured from existing sources and new innovations such as streaming and IoT — businesses have needed to find creative ways of managing their increasingly complex data lifecycle to speed time to insight. Accelerate Collaboration Across The Lifecycle.

Machine Learning 110

Machine Learning Unstructured Data Data Warehouse Government 110

Cloudera

FEBRUARY 8, 2024

Cloudera Data Warehouse (CDW) running Hive has previously supported creating materialized views against Hive ACID source tables. Starting from the CDW Public Cloud DWX-1.6.1 We ran the fifty query workload on a CDW Hive virtual warehouse on AWS using a large t-shirt size (see Virtual Warehouse sizes ).

Metadata 89

Metadata Data Warehouse BI AWS 89

Data Engineering Weekly

FEBRUARY 18, 2024

[link] Joe Reis: Everything Ends - My Journey With the Modern Data Stack Joe writes another excellent retrospect for Modern Data Stack, walking down memory lane of the early and golden days of the Modern Data Stack. We are so over the Big Data Era to Modern Data Stack.

Data Engineering 62

Data Engineering Data Engineer Engineering Data 62

Data Engineering Weekly

DECEMBER 4, 2022

The author narrates why the data models are still important for managing data assets' structure, content, and relationships but also need to keep agility in mind to bring business velocity. The article highlights the challenges of maintaining data models in a world where SQL data warehouses are no longer the primary data platform.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Data Engineering Weekly

MAY 19, 2024

link] Sponsored: Build next-generation data experiences faster with Cube Cloud Join us for a live webinar on May 22nd at 9 am PT | 12 pm ET, where we'll showcase how to accelerate the development of AI and embedded analytics solutions using Cube Cloud. Register now and join us on May 22nd!

Data Engineering 52

Data Engineering Data Engineer Engineering Kafka 52

Data Engineering Weekly

FEBRUARY 19, 2023

Design a mock data Find the data Assess Data Quality and Consistency Assess Model freshness Assess Model performance [link] Sponsored: Replacing GA4 with Analytics on your Data Cloud The GA4 migration deadline is fast approaching. Join our webinar to learn how you can replace GA with analytics on your data cloud.

Data Engineering 52

Data Engineering Data Engineer Engineering Google Cloud 52

Cloudera

DECEMBER 19, 2018

Business intelligence (BI), an umbrella term coined in 1989 by Howard Dresner, Chief Research Officer at Dresner Advisory Services, refers to the ability of end-users to access and analyze enterprise data. Natural language analytics and streaming data analytics are emerging technologies that will impact the market. Cloud Computing.

BI 51

BI Cloud Computing Data Warehouse Big Data 51

Cloudera

DECEMBER 14, 2020

We’ve seen organizations invest in big data solutions, and now, we’ve increasingly seen them want to build on that investment and move towards building a modern architecture that’ll help them leverage stream processing and streaming analytics. Cloudera Data Platform (CDP) is the new data cloud built for the enterprise.

Process 70

Process Kafka Government Big Data 70

Data Engineering Weekly

AUGUST 20, 2023

The blog narrates the potential possibilities of LLM’s impact in each stage of the data warehouse. link] Sponsored: Great Data Debate–The State of Data Mesh Since 2019, the data mesh has woven itself into every blog post, event presentation, and webinar.

Data Engineering 52

Data Engineering Data Engineer Engineering Data 52

Knowledge Hut

NOVEMBER 28, 2023

The contemporary world experiences a huge growth in cloud implementations, consequently leading to a rise in demand for data engineers and IT professionals who are well-equipped with a wide range of application and process expertise. This can be easier when you are using existing cloud services.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Cloudera

DECEMBER 21, 2020

In this blog we will take you through a persona-based data adventure, with short demos attached, to show you the A-Z data worker workflow expedited and made easier through self-service, seamless integration, and cloud-native technologies. In our data adventure we assume the following: . The Data Scientist.

Banking 97

Banking Data Lake Data Data Warehouse 97

Data Engineering Weekly

FEBRUARY 26, 2023

[link] Matt Turck: The 2023 MAD (Machine Learning, Artificial Intelligence & Data) Landscape It’s time for Matt’s 2023 MAD landscape with 1,416 logos, up from 139 in 2012. Perhaps merge Data LakeHouse & Data Warehouse in the next edition? The gap is blurring between them.

Data Engineering 57

Data Engineering Data Engineer Engineering Raw Data 57

Data Engineering Weekly

MARCH 10, 2024

Big thanks to our insightful speakers, Hareshkumar Selvakumar - Talks about his work on Data Products for PayPal. Pradheep Arjunan - Shared insights on AZ's journey from on-prem to the cloud data warehouses. Thanks to Ideas2IT Technologies for hosting us in their fantastic space.

Data Engineering 52

Data Engineering Data Engineer Engineering Datasets 52

Monte Carlo

JUNE 14, 2023

Some organizations choose to still leverage an ETL pattern in the cloud, particularly for production pipelines where data contracts can help reduce data downtime. With cost and physical compute/storage limitations largely lifted, data engineers started to optimize data pipeline architecture for speed and agility.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

NOVEMBER 2, 2020

Users today are asking ever more from their data warehouse. As an example of this, in this post we look at Real Time Data Warehousing (RTDW), which is a category of use cases customers are building on Cloudera and which is becoming more and more common amongst our customers. What is Real Time Data Warehousing?

Data Warehouse 95

Data Warehouse Kafka Lambda Architecture Telecommunication 95

Cloudera

JULY 14, 2023

While these instructions are carried out for Cloudera Data Platform (CDP), Cloudera Data Engineering, and Cloudera Data Warehouse, one can extrapolate them easily to other services and other use cases as well. CONS This will trigger a full read and write of the data and it might be an expensive operation.

Metadata 69

Metadata Data Warehouse Big Data Ecosystem Java 69

Rockset

OCTOBER 27, 2020

Instead of being free to build the apps their businesses require, developers are often held back by the limitations of their data infrastructure. Building large-scale data applications with traditional OLTP databases or data warehouses left developers with two frustrating choices.

Building 40

Building Data Warehouse Transportation Retail 40

Cloudera

DECEMBER 20, 2022

Going into more technological aspects, the data platforms that must support this decision-making must be able to operate in a hybrid environment in which there is integration with the applications that reside in the company’s own data centers, as well as the possibility of working in public cloud environments. .

Data Analytics 79

Data Analytics Retail Machine Learning Recruitment 79

Rockset

JANUARY 28, 2022

Wealth of Data, Little Observability Those metrics included the data generated by existing and new Seesaw users as they interacted with the service. Storing all of that data was not a problem. Seesaw was able to scale up its main database, an Amazon DynamoDB cloud-based service optimized for large datasets.

NoSQL 52

NoSQL PostgreSQL MongoDB ETL Tools 52

Knowledge Hut

JANUARY 24, 2024

Supports numerous data sources It connects to and fetches data from a variety of data sources using Tableau and supports a wide range of data sources, including local files, spreadsheets, relational and non-relational databases, data warehouses, big data, and on-cloud data.

BI 98

BI Business Intelligence Non-relational Database Data Analysis 98

Cloudera

MAY 22, 2018

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. In addition to cloud options, customers can now deploy on premises with Oracle Linux 7.4 (for for the Oracle Big Data Appliance).

Data Science 41

Data Science Machine Learning Big Data Metadata 41

Cloudera

JANUARY 11, 2021

Here are some details to consider: NiFi is designed to be centrally located, usually in a data center or in the cloud, to move data around or collect data from well-known external systems like databases, object stores, etc. Such systems can be NiFi of course, but also MQTT brokers, cloud providers services, etc.

Kafka 62

Kafka Java Data Cleanse Datasets 62

AltexSoft

NOVEMBER 7, 2022

So you can quickly link to many popular databases, cloud services, and other tools — such as MySQL, PostgreSQL, HDFS ( Hadoop distributed file system), Oracle, AWS, Google Cloud, Microsoft Azure, Snowflake, Slack, Tableau , and so on. The Good and the Bad of Power BI Data Visualization. How to get started with Apache Airflow?

PostgreSQL 52

PostgreSQL Metadata Python MySQL 52

Databand.ai

DECEMBER 29, 2022

Follow Ravit on LinkedIn 5) Priya Krishnan Head of Product Management, Data and AI at IBM Priya is an innovative, customer-focused, data-driven product executive with over 16 years of experience in global product management, strategy, and GTM roles to commercialize and monetize in-demand enterprise solutions.

BI 52

BI Consulting Data Science Data Governance 52

Knowledge Hut

DECEMBER 21, 2023

What is Data Engineering? Data engineering is the method to collect, process, validate and store data. It involves building and maintaining data pipelines, databases, and data warehouses. The purpose of data engineering is to analyze data and make decisions easier.

Data Engineering 52

Data Engineering Data Engineer Engineering MongoDB 52

Snowflake

JULY 22, 2024

A three-phase approach to expanding data platform capabilities Enterprises may face a slowdown in their data platform maturity journey after migrating their legacy data systems to a cloud-based data platform, especially when using a lift-and-shift approach.

Government 98

Government Data Cloud Hadoop 98

Snowflake

NOVEMBER 11, 2024

Those requirements can be fulfilled by leveraging cloud infrastructure and services. Such collaborative data sharing would create a more fortified ecosystem, where the collective intelligence of the many provides a stronger line of defense than any single institution or small group could achieve alone.”

Banking 76

Banking Finance Retail Food 76

Cloudera

NOVEMBER 27, 2023

By democratizing access to streaming data, and bringing domain expert users into the development cycle, we help accelerate iterations on stream processing applications. This is vital when onboarding new data, or changing logic to meet evolving needs as is the case in fraud monitoring. Takeaway No. Hybrid matters!

Kafka 83

Kafka SQL ETL Tools Architecture 83

Monte Carlo

MAY 17, 2023

Data Warehouse (Or Lakehouse) Migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. “We Another common breaking schema change scenario is when data teams sync their production database with their data warehouse as is the case with Freshly.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52