Cloudera

AUGUST 17, 2022

?. What if you could access all your data and execute all your analytics in one workflow, quickly with only a small IT team? CDP One is a new service from Cloudera that is the first data lakehouse SaaS offering with cloud compute, cloud storage, machine learning (ML), streaming analytics, and enterprise grade security built-in.

Cloud Computing 115

Cloud Computing Cloud Storage Data Science Government 115

phData: Data Engineering

SEPTEMBER 19, 2023

Cost reduction by minimizing data redundancy, improving data storage efficiency, and reducing the risk of errors and data-related issues. Data Governance and Security By defining data models, organizations can establish policies, access controls, and security measures to protect sensitive data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Towards Data Science

JULY 24, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 96

Metadata Data Warehouse Data Lake Data Science 96

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Engineering 92

Data Engineering Data Engineer Cloud Engineering 92

Cloudera

AUGUST 26, 2021

This means that there is out of the box support for Ozone storage in services like Apache Hive , Apache Impala, Apache Spark, and Apache Nifi, as well as in Private Cloud experiences like Cloudera Machine Learning (CML) and Data Warehousing Experience (DWX). Data ingestion through ‘s3’. Spark SQL to access Hive table.

Data Science 111

Data Science Cloud Hadoop Metadata 111

Cloudera

SEPTEMBER 9, 2022

The promise of a modern data lakehouse architecture. Imagine having self-service access to all business data, anywhere it may be, and being able to explore it all at once. Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested.

Architecture 100

Architecture Metadata Unstructured Data Machine Learning 100

Towards Data Science

DECEMBER 1, 2023

The data volume we will deal with is small, so we will not try to overkill with data partitioning, time travel, Snowpark, and other Snowflake advanced capabilities. However, we will pay particular attention to Access Control (this will be used for dbt access). There are two ways to access dbt: dbt Cloud and dbt Core.

Data Engineering 71

Data Engineering Data Engineer Project Engineering 71

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 86

Data Lake Business Intelligence Metadata Data Warehouse 86

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Monte Carlo

NOVEMBER 14, 2023

Databricks announced that Delta tables metadata will also be compatible with the Iceberg format, and Snowflake has also been moving aggressively to integrate with Iceberg. How Apache Iceberg tables structure metadata. Without a central query log, your team can run the risk of data loss and lack of data governance.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Monte Carlo

MARCH 28, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Warehouse 126

Data Warehouse Raw Data Data Pipeline Software Engineer 126

Cloudera

MARCH 31, 2021

Customers who have chosen Google Cloud as their cloud platform can now use CDP Public Cloud to create secure governed data lakes in their own cloud accounts and deliver security, compliance and metadata management across multiple compute clusters. Data Preparation (Apache Spark and Apache Hive) .

Google Cloud 92

Google Cloud Cloud Amazon Web Services Cloud Storage 92

Cloudera

JUNE 16, 2022

Faster data ingestion: streaming ingestion pipelines. Kafka blindness is the enterprise’s struggle to monitor, troubleshoot, heal, govern, secure, and provide disaster recovery for Apache Kafka clusters. . She is a smart data analyst and former DBA working at a planet-scale manufacturing company. Who is affected?

Kafka 86

Kafka Manufacturing Data Lake SQL 86

Monte Carlo

AUGUST 19, 2023

By integrating tools from a variety of vendors, a data platform enables a data engineering team to not only manage an organization’s data but also activate it for a domain’s use cases. In today’s data-driven landscape, building a data platform is no longer a nice-to-have, but a necessity for most organizations.

Building 52

Building BI Data Lake Data Governance 52

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

FEBRUARY 16, 2022

Model interpretability is one of five main components of model governance. In this article, we explore model governance, a function of ML Operations (MLOps). Within the CML data service, model lineage is managed and tracked at a project level by the SDX. blueberry spacing) is a measure of the model’s interpretability.

Machine Learning 83

Machine Learning Algorithm Government Metadata 83

Monte Carlo

JULY 18, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 52

Metadata Data Warehouse Data Lake Government 52

Towards Data Science

APRIL 3, 2023

And so it almost seems unfair that new ideas are already springing up to disrupt the disruptors: Zero-ETL has data ingestion in its sights AI and Large Language Models could transform transformation Data product containers are eyeing the table’s thrown as the core building block of data Are we going to have to rebuild everything (again)?

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

Cloudera

FEBRUARY 8, 2021

ECC will enrich the data collected and will make it available to be used in analysis and model creation later in the data lifecycle. Below is the entire set of steps in the data lifecycle, and each step in the lifecycle will be supported by a dedicated blog post(see Fig. 1 The enterprise data lifecycle.

Data Pipeline 116

Data Pipeline Building Manufacturing Data Warehouse 116

Snowflake

MAY 22, 2023

Cross-Cloud Snowgrid Account Replication expands replication beyond databases – general availability Account Replication, now generally available, expands replication beyond databases to account metadata and integrations, making business continuity truly turnkey. Learn more here. Visit our documentation page to learn more. Learn more.

Healthcare 52

Healthcare Scala Medical Transportation 52

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. Thus, the data mesh follows the seams of organizational units. So, what’s the solution?

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

Data represents our present and our future, and therein lies a significant problem: the more data you’re dealing with, the more challenging it will be to scale your company in a sustainable and standardized way. Thus, the data mesh follows the seams of organizational units. So, what’s the solution?

Government 52

Government Architecture Data Lake Data 52

Monte Carlo

JULY 18, 2023

Closely related to this is how those same platforms are bundling or unbundling related data services from data ingestion and transformation to data governance and monitoring. Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 40

Metadata Data Warehouse Data Lake Government 40

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Most organizations deploy some or all of these data pipeline architectures.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Cloudera

SEPTEMBER 28, 2020

Cloudera delivers an enterprise data cloud that enables companies to build end-to-end data pipelines for hybrid cloud, spanning edge devices to public or private cloud, with integrated security and governance underpinning it to protect customers data. Data Science and machine learning workloads using CDSW.

Cloud 131

Cloud Kafka Professional Services Metadata 131

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Most modern platforms expose public or private APIs as a way to access their data directly.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Databand.ai

JUNE 28, 2023

Yet reality is of course more closely governed by Murphy’s law, and on the output side of the black box, you will often see a host of strange values and cryptic missing columns. Data engineers are scratching their heads and realizing that to correct, you must first observe. And why the discrepancy? See Databand in action Databand.ai

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

AltexSoft

MARCH 14, 2023

That’s why some MDS tools are commercial distributions designed to be low-code or even no-code, making them accessible to data practitioners with minimal technical expertise. This means that companies don’t necessarily need a large data engineering team. Data democratization.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Cloudera

AUGUST 31, 2021

It outperforms other data warehouses on all sizes and types of data, including structured and unstructured, while scaling cost-effectively past petabytes. Running on CDW is fully integrated with streaming, data engineering, and machine learning analytics. Consideration of both data & metadata in the migration.

Data Warehouse 82

Data Warehouse Database-centric Metadata Cloud 82

AltexSoft

MARCH 30, 2023

Databricks architecture Databricks provides an ecosystem of tools and services covering the entire analytics process — from data ingestion to training and deploying machine learning models. Besides that, it’s fully compatible with various data ingestion and ETL tools. Let’s see what exactly Databricks has to offer.

Scala 64

Scala Data Lake BI Google Cloud 64

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 84

Engineering Raw Data Data Science Scala 84

AltexSoft

MAY 12, 2023

Tools and platforms for unstructured data management Unstructured data collection Unstructured data collection presents unique challenges due to the information’s sheer volume, variety, and complexity. The process requires extracting data from diverse sources, typically via APIs. Data durability and availability.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

JULY 29, 2022

According to the latest report by Allied Market Research , the Big Data platform will see the biggest rise in adoption in telecommunication, healthcare, and government sectors. Instruments like Apache ZooKeeper and Apache Oozie help better coordinate operations, schedule jobs, and track metadata across a Hadoop cluster.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Cloudera

JANUARY 22, 2019

Pragmatically, Big Data Fabric comprises the following 6 layers that work harmoniously to provide seamless, real-time integration of Big Data: Data ingestion. Data processing and persistence. Data orchestration. Data discovery. Data management and intelligence. Data access.

Big Data 44

Big Data NoSQL Data Lake Hadoop 44

Monte Carlo

JULY 10, 2023

Accuracy reflects the degree to which the data correctly describes the “real-world” objects being described. For example, let’s say a streaming provider has 10 million overall subscribers who can access its content. According to the CRM’s data set, the streaming provider has 13 million subscribers.

Data Collection 40

Data Collection Data Governance Government Data 40

phData: Data Engineering

AUGUST 4, 2023

Data storage is a vital aspect of any Snowflake Data Cloud database. Within Snowflake, data can either be stored locally or accessed from other cloud storage systems. Snowflake hides user data objects and makes them accessible only through SQL queries through the compute layer.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52