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 66

Data Strategy Strategy Data Warehouse Prescriptive Analytics 66

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

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 128

Unstructured Data Data-driven Visualization Data Quality 128

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

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 93

Data Lake Data Warehouse IT Analytics 93

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

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 143

Management Advertising Data Lake Sales 143

Cloudera

FEBRUARY 4, 2019

With the rise of streaming architectures and digital transformation initiatives everywhere, enterprises are struggling to find comprehensive tools for data management to handle high volumes of high-velocity streaming data. CDF can do this within a common framework that offers unified security, governance and management.

IoT 73

IoT Prescriptive Analytics Digital Transformation Internet of Things 73

Darkhorse

JULY 6, 2017

You see, 80% of your working hours will be spent wrangling the data. So what is data wrangling? Let’s imagine the process of building a data lake. First off, data wrangling is gathering the appropriate data. You’ve got yourself a little data lake, but its waters are brackish. Proceed visually.

Data Lake 74

Data Lake Sales Machine Learning Visualization 74

datapine

AUGUST 29, 2022

The new edition also explores artificial intelligence in more detail, covering topics such as Data Lakes and Data Sharing practices. 6) Lean Analytics: Use Data to Build a Better Startup Faster, by Alistair Croll and Benjamin Yoskovitz. Khan Analytic Philosophy: A Very Short Introduction by Michael Beaney.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Cloudera

NOVEMBER 22, 2021

In addition, data pipelines include more and more stages, thus making it difficult for data engineers to compile, manage, and troubleshoot those analytical workloads. CRM platforms). CRM platforms).

Data Processing 90

Data Processing Data Warehouse Enterprise Visualization 90

Alation

FEBRUARY 17, 2023

Reichental describes data governance as the overarching layer that empowers people to manage data well ; as such, it is focused on roles & responsibilities, policies, definitions, metrics, and the lifecycle of the data. In this way, data governance is the business or process side. Where do you govern?

Data Governance 52

Data Governance Data Quality Metadata Cost-Benefit 52

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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