Cloudera

DECEMBER 20, 2021

In the past year, the Bank of the West has begun using the Cloudera platform to establish a data governance and security framework to manage and protect its customers’ sensitive information. The platform is centralizing the data, data management & governance, and building custom controls for data ingestion into the system.

Government 89

Government Data Security Banking Metadata 89

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’. Ozone Namespace Overview.

Data Science 111

Data Science Cloud Hadoop Metadata 111

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

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

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? Data-first companies have embraced data platforms as an effective way to aggregate, operationalize, and democratize data at scale across the organization. The five must-have layers of a modern data platform Second to “how do I build my data platform?”,

Building 52

Building BI Data Lake Data Governance 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 52

Metadata Data Warehouse Data Lake Government 52

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

AltexSoft

MARCH 14, 2023

Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. What is a modern data stack? A data stack, in turn, focuses on data : It helps businesses manage data and make the most out of it. Modern data stack architecture.

IT 59

IT Data Warehouse Data Governance Data Lake 59

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. Read our articles on structured vs unstructured data and unstructured data to learn more.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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

AltexSoft

MARCH 30, 2023

It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data. The relatively new storage architecture powering Databricks is called a data lakehouse. Databricks lakehouse platform architecture.

Scala 64

Scala Data Lake BI Google Cloud 64

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. It provides a more distributed, decentralized, and resilient approach to data management. 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. It provides a more distributed, decentralized, and resilient approach to data management. So, what’s the solution?

Government 52

Government Architecture Data Lake Data 52

ProjectPro

AUGUST 24, 2021

If you are a newbie in data engineering and are interested in exploring real-world data engineering projects, check out the list of best data engineering project examples below. With the trending advance of IoT in every facet of life, technology has enabled us to handle a large amount of data ingested with high velocity.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

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. Build data architecture.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

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 83

Engineering Raw Data Data Science Scala 83

phData: Data Engineering

JULY 18, 2023

Enterprises can effortlessly prepare data and construct ML models without the burden of complex integrations while maintaining the highest level of security. Generally, organizations need to integrate a wide variety of source systems when building their analytics platform, each with its own specific data extraction requirements.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

phData: Data Engineering

AUGUST 4, 2023

Database Storage The Snowflake architecture’s database storage layer organizes data into multiple tiny partitions, which are compressed and optimized internally. Snowflake stores and manages data in the cloud using a shared disk approach, which simplifies data management.

Cloud Storage 52

Cloud Storage Google Cloud Amazon Web Services Data Storage 52

ProjectPro

NOVEMBER 15, 2021

Apache Zeppelin Source: Github Apache Zeppelin is a multi-purpose notebook that supports Data Ingestion, Data Discovery, Data Analytics , Data Visualization , and Data Collaboration. Furthermore, Cassandra is a NoSQL database in which all nodes are peers, rather than master-slave architecture.

Big Data 52

Big Data Project Metadata Programming Language 52