DataKitchen

OCTOBER 11, 2021

Figure 2: Example data pipeline with DataOps automation. In this project, I automated data extraction from SFTP, the public websites, and the email attachments. The automated orchestration published the data to an AWS S3 Data Lake. Monitoring Job Metadata.

Testing 154

Testing Metadata Dashboards Statistics 154

Cloudera

JUNE 16, 2022

Organizations are increasingly building low-latency, data-driven applications, automations, and intelligence from real-time data streams. Cloudera Stream Processing (CSP) enables customers to turn streams into data products by providing capabilities to analyze streaming data for complex patterns and gain actionable intel.

Data Lake 88

Data Lake Manufacturing Metadata Dashboards 88

AWS Big Data

APRIL 19, 2023

We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The first component (metadata setup) consumes existing Hive job configurations and generates metadata such as number of parameters, number of actions (steps), and file formats. sql_path SQL file name.

Metadata 98

Metadata Data Lake Testing Consulting 98

CIO Business Intelligence

SEPTEMBER 22, 2023

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. Roku OneView The brand name may be more familiar as a streaming video device manufacturer, but Roku also places ads.

Management 105

Management Advertising Data Lake Sales 105

AWS Big Data

MARCH 25, 2024

You can find similar use cases in other industries such as retail, car manufacturing, energy, and the financial industry. In this post, we discuss why data streaming is a crucial component of generative AI applications due to its real-time nature.

Data Lake 122

Data Lake Unstructured Data Management Snapshot 122

IBM Big Data Hub

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.) But the implementation of AI is only one piece of the puzzle.

Cost-Benefit 76

Cost-Benefit Metadata Data Governance Optimization 76

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: workload analysis and replication, migrating or bursting to cloud, data warehouse optimization, and more. Should you find yourself looking for inspiration for your entry, we encourage you to have a look at the incredible work of last year’s data superheroes.

Digital Transformation 70

Digital Transformation Machine Learning Optimization Data Lake 70

CIO Business Intelligence

JANUARY 30, 2024

Even for more straightforward ESG information, such as kilowatt-hours of energy consumed, ESG reporting requirements call for not just the data, but the metadata, including “the dates over which the data was collected and the data quality,” says Fridrich. “The complexity is at a much higher level.”

Reporting 115

Reporting Data Quality Strategy Data-driven 115

AWS Big Data

AUGUST 6, 2024

In parallel, the Pinot controller tracks the metadata of the cluster and performs actions required to keep the cluster in an ideal state. Its primary function is to orchestrate cluster resources as well as manage connections between resources within the cluster and data sources outside of it.

OLAP 111

OLAP Analytics Visualization Dashboards 111

Cloudera

NOVEMBER 12, 2020

Inability to maintain context – This is the worst of them all because every time a data set or workload is re-used, you must recreate its context including security, metadata, and governance. Alternatively, you can also spin up a different compute cluster and access the data by using CDP’s Shared Data Experience.

Data Warehouse 104

Data Warehouse Reporting Risk Cost-Benefit 104

bridgei2i

MARCH 3, 2021

Prinkan: Yeah, one of them, I think, which we are currently working on is with a global electronics manufacturing company, where they are trying to implement a customer 360 platform to enable purpose-based search or recommendations, more than a feature basis. Pavan: Really fascinating discussion, Prinkan.

Enterprise 98

Enterprise Digital Transformation Data-driven Interactive 98

Andrew White

OCTOBER 22, 2021

Manufacturer (process or discrete) 8. Lakehouse (data warehouse and data lake working together) 8. Data Literacy, training, coordination, collaboration 8. Data Management Infrastructure/Data Fabric 5. Data Integration tactics 4. Metadata Strategy 3. Financial Services 4. Healthcare 4.

IT 52

IT Data Lake Data Science Strategy 52

Cloudera

JUNE 4, 2018

The solution to this massive data challenge embedded the Aspire Content Processing Framework into the Cloudera Enterprise Data Hub as a Cloudera Parcel – a binary distribution format containing the program files, along with additional metadata used by Cloudera Manager.

Unstructured Data 46

Unstructured Data Metadata Big Data Enterprise 46

In(tegrate) the Clouds

DECEMBER 21, 2015

Aside from the Internet of Things, which of the following software areas will experience the most change in 2016 – big data solutions, analytics, security, customer success/experience, sales & marketing approach or something else? 2016 will be the year of the data lake. Is Netflix considered a software company these days?

Technology 45

Technology Internet of Things Digital Transformation Big Data 45

Alation

FEBRUARY 20, 2020

In the back office and manufacturing, organizations invested in enterprise resource planning (ERP) software. Today, CDOs in a wide range of industries have a mechanism for empowering their organizations to leverage data. As data initiatives mature, the Alation data catalog is becoming central to an expanding set of use cases.

Data-driven 52

Data-driven Internet of Things Data Lake Strategy 52

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Machine Learning 52

Andrew White

JANUARY 11, 2021

As such banking, finance, insurance and media are good examples of information-based industries compared to manufacturing, retail, and so on. Does Data warehouse as a software tool will play role in future of Data & Analytics strategy? Data lakes don’t offer this nor should they.

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52

AWS Big Data

MARCH 13, 2025

StarTrees automatic data ingestion framework is ideal for enterprise workloads because it improves scalability and reduces the data maintenance complexity often found in open source Pinot deployments. The data is then modelled to help you organize and structure the data fetched from the selected data source into Pinot tables.

Management 105

Management Analytics OLAP Online Analytical Processing 105

AWS Big Data

FEBRUARY 10, 2025

First, many data warehousing use cases involve processing petabyte-sized historical datasets, whether for initial data loading or periodic reprocessing and querying. This level of complex data processing requires substantial memory and parallel processing capabilities that can be effectively provided by a 1024 RPU configuration.

Data Warehouse 103

Data Warehouse Cost-Benefit Data Lake Optimization 103

AWS Big Data

NOVEMBER 14, 2024

Amazon Data Firehose – Data Firehose is an extract, transform, and load (ETL) service that reliably captures, transforms, and delivers streaming data to data lakes, data stores, and analytics services. AWS Glue – The AWS Glue Data Catalog is your persistent technical metadata store in the AWS Cloud.

Data Lake 105

Data Lake Metadata Testing Data-driven 105

CIO Business Intelligence

MAY 6, 2025

Customer data in Salesforce, product usage data in Snowflake and financials in Oracle none integrated Regional systems using different naming conventions and field formats This fragmentation leads to inconsistent definitions, duplication of work and multiple versions of the truth.

Prescriptive Analytics 78

Prescriptive Analytics Predictive Analytics Descriptive Analytics ROI 78