Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 85

Machine Learning Modeling Metadata Recreation/Entertainment 85

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

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. Towards Data Science ). Forrester ). Gartner ).

Data Architecture 79

Data Architecture Data Lake Metadata Data Warehouse 79

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

Cloudera

JANUARY 21, 2021

Storing data in a proprietary, single-workload solution also recreates dangerous data silos all over again, as it locks out other types of workloads over the same shared data. The Data Lake service in Cloudera’s Data Platform provides a central place to understand, manage, secure, and govern data assets across the enterprise.

Data Lake 94

Data Lake Data Warehouse IT Analytics 94

CIO Business Intelligence

SEPTEMBER 22, 2023

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 105

Management Advertising Data Lake Sales 105

Cloudera

DECEMBER 8, 2020

Federated Learning is a paradigm in which machine learning models are trained on decentralized data. Instead of collecting data on a single server or data lake, it remains in place — on smartphones, industrial sensing equipment, and other edge devices — and models are trained on-device.

Machine Learning 85

Machine Learning Data Lake Reporting Modeling 85

CIO Business Intelligence

MAY 26, 2022

Enterprises that are just starting to move to this discipline should keep in mind that at its core MLOps is about creating strong connections between data science and data engineering. “To To ensure the success of an MLOps project, you need both data engineers and data scientists on the same team,” Zuccarelli says.

Machine Learning 145

Machine Learning Modeling Data-driven Dashboards 145

datapine

AUGUST 29, 2022

Best for : the new intern who has no idea what data science even means. An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

CIO Business Intelligence

MAY 28, 2022

Enterprises that are just starting to move to this discipline should keep in mind that at its core MLOps is about creating strong connections between data science and data engineering. “To To ensure the success of an MLOps project, you need both data engineers and data scientists on the same team,” Zuccarelli says.

Machine Learning 143

Machine Learning Modeling Data-driven Dashboards 143

CIO Business Intelligence

NOVEMBER 28, 2023

With each game release and update, the amount of unstructured data being processed grows exponentially, Konoval says. This volume of data poses serious challenges in terms of storage and efficient processing,” he says. To address this problem RetroStyle Games invested in data lakes. Ensure value with visualizations.

Unstructured Data 130

Unstructured Data Data-driven Visualization Data Quality 130

Alation

JULY 7, 2022

To answer these questions we need to look at how data roles within the job market have evolved, and how academic programs have changed to meet new workforce demands. In the 2010s, the growing scope of the data landscape gave rise to a new profession: the data scientist. A lack of data literacy slows down the process.

Metadata 52

Metadata Data-driven Insurance Statistics 52

AWS Big Data

FEBRUARY 21, 2023

The data vault approach is a method and architectural framework for providing a business with data analytics services to support business intelligence, data warehousing, analytics, and data science needs. Amazon Redshift RA3 instances and Amazon Redshift Serverless are perfect choices for a data vault.

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Metadata 66

Alation

FEBRUARY 17, 2023

The firms that get data governance and management “right” bring people together and leverage a set of capabilities: (1) Agile; (2) Six sigma; (3) data science; and (4) project management tools. Can you differentiate between governance of raw data and enhanced data (information)? Where do you govern?

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52