IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? What is machine learning?

Machine Learning 60

Machine Learning Data Science Statistics Deep Learning 60

IBM Big Data Hub

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

Machine Learning 51

Machine Learning Marketing Forecasting Modeling 51

AWS Big Data

MARCH 27, 2023

Amazon Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure. He works with customers and engineering teams to build new features that enable data engineers and data analysts to more easily load data, manage data warehouse resources, and query their data.

Data Warehouse 81

Data Warehouse Management Snapshot Data Lake 81

Cloudera

JANUARY 15, 2021

Cloud data warehouses allow users to run analytic workloads with greater agility, better isolation and scale, and lower administrative overhead than ever before. The results demonstrate superior price performance of Cloudera Data Warehouse on the full set of 99 queries from the TPC-DS benchmark. Introduction.

Data Warehouse 90

Data Warehouse Cost-Benefit Consulting Interactive 90

David Menninger's Analyst Perspectives

SEPTEMBER 16, 2021

Rapidminer is a visual enterprise data science platform that includes data extraction, data mining, deep learning, artificial intelligence and machine learning (AI/ML) and predictive analytics. Rapidminer Studio is its visual workflow designer for the creation of predictive models.

Data Science 319

Data Science Data Lake Data mining Deep Learning 319

Cloudera

DECEMBER 11, 2020

In this blog post, we compare Cloudera Data Warehouse (CDW) on Cloudera Data Platform (CDP) using Apache Hive-LLAP to EMR 6.0 (also powered by Apache Hive-LLAP) on Amazon using the TPC-DS 2.9 Cloudera Data Warehouse vs EMR. Learn more about Cloudera Data Warehouse on CDP.

Data Warehouse 106

Data Warehouse Metadata Machine Learning Measurement 106

Cloudera

FEBRUARY 16, 2022

In this example, the Machine Learning (ML) model struggles to differentiate between a chihuahua and a muffin. We will learn what it is, why it is important and how Cloudera Machine Learning (CML) is helping organisations tackle this challenge as part of the broader objective of achieving Ethical AI.

Machine Learning 81

Machine Learning Modeling Metadata Recreation/Entertainment 81

erwin

JUNE 7, 2022

Designing databases for data warehouses or data marts is intrinsically much different than designing for traditional OLTP systems. Accordingly, data modelers must embrace some new tricks when designing data warehouses and data marts. Figure 1: Pricing for a 4 TB data warehouse in AWS.

Data Warehouse 52

Data Warehouse Modeling Sales Data Lake 52

O'Reilly on Data

FEBRUARY 19, 2021

MLOps attempts to bridge the gap between Machine Learning (ML) applications and the CI/CD pipelines that have become standard practice. The Time Is Now to Adopt Responsible Machine Learning. Data use is no longer a “wild west” in which anything goes; there are legal and reputational consequences for using data improperly.

Data Lake 289

Data Lake Data Warehouse Machine Learning Modeling 289

Jen Stirrup

MAY 5, 2020

It has native integration with other data sources, such as SQL Data Warehouse, Azure Cosmos, database storage, and even Azure Blob Storage as well. When you’re using Big Data technologies, it’s often a concern about how well those are performing in terms of performance and robustness. Azure Machine Learning.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

O'Reilly on Data

AUGUST 18, 2020

That is, products that are laser-focused on one aspect of the data science and machine learning workflows, in contrast to all-in-one platforms that attempt to solve the entire space of data workflows. Lessons Learned from Data Warehouse and Data Engineering Platforms. A little of both?

Data Science 355

Data Science Machine Learning Data Warehouse Deep Learning 355

CDW Research Hub

JULY 22, 2019

Companies today are struggling under the weight of their legacy data warehouse. These old and inefficient systems were designed for a different era, when data was a side project and access to analytics was limited to the executive team. To do so, these companies need a modern data warehouse, such as Snowflake.

Data Warehouse 54

Data Warehouse Business Intelligence Structured Data Data Architecture 54

CIO Business Intelligence

MARCH 29, 2024

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. Today, 60% to 70% of Rocket’s workloads run on the cloud, with more than 95% of those workloads in AWS.

Data Lake 121

Data Lake Machine Learning Data Warehouse Unstructured Data 121

AWS Big Data

APRIL 10, 2024

“Data is at the center of every application, process, and business decision. Customers across industries are becoming more data driven and looking to increase revenue, reduce cost, and optimize their business operations by implementing near real time analytics on transactional data, thereby enhancing agility.

Data Warehouse 88

Data Warehouse Analytics Metrics Snapshot 88

Alation

FEBRUARY 13, 2020

Human Curation + Machine Learning. The way Herschel, Fry, and Zimmerman talked about AI in many respects reflects our vision for machine learning data catalogs. What’s more, Zaidi and Gartner believe that this vision of a machine-learning-enabled data catalog creates real value for enterprises.

Machine Learning 52

Machine Learning Data Analytics Analytics Metadata 52

Analytics Vidhya

FEBRUARY 20, 2022

This article was published as a part of the Data Science Blogathon. Introduction Apache Hive is a data warehouse system built on top of Hadoop which gives the user the flexibility to write complex MapReduce programs in form of SQL- like queries.

Data Warehouse 320

Data Warehouse Data Science Publishing Analytics 320

David Menninger's Analyst Perspectives

NOVEMBER 16, 2021

Talend data integration software offers an open and scalable architecture and can be integrated with multiple data warehouses, systems and applications to provide a unified view of all data. Its code generation architecture uses a visual interface to create Java or SQL code.

Management 311

Management Data Warehouse Data Quality Data Integration 311

Smart Data Collective

APRIL 8, 2020

Dating back to the 1970s, the data warehousing market emerged when computer scientist Bill Inmon first coined the term ‘data warehouse’. Created as on-premise servers, the early data warehouses were built to perform on just a gigabyte scale. Cloud based solutions are the future of the data warehousing market.

Technology 134

Technology Data Warehouse Big Data Machine Learning 134

IBM Big Data Hub

OCTOBER 1, 2018

The IBM Integrated Analytics System (IIAS), is a unique, cloud-ready appliance and machine learning platform wields the power of an in-memory, massively parallel processing database engine with embedded Spark.

Data Warehouse 72

Data Warehouse Machine Learning Big Data Optimization 72

AWS Big Data

NOVEMBER 28, 2023

To run analytics on their operational data, customers often build solutions that are a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 89

Data Warehouse Data-driven Machine Learning B2B 89

Analytics Vidhya

FEBRUARY 6, 2023

Introduction The demand for data to feed machine learning models, data science research, and time-sensitive insights is higher than ever thus, processing the data becomes complex. To make these processes efficient, data pipelines are necessary.

Machine Learning 271

Machine Learning Data Science Modeling Analytics 271

David Menninger's Analyst Perspectives

OCTOBER 5, 2021

The platform features tools to run a variety of analytic functions such as diagnostic, predictive, prescriptive and geospatial analytics in a unified platform, and can connect to various data warehouses, cloud applications, spreadsheets and other sources.

Analytics 274

Analytics Data Warehouse Software Modeling 274

IBM Big Data Hub

APRIL 25, 2023

To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures. Now, let’s chat about why data warehouse optimization is a key value of a data lakehouse strategy. To effectively use raw data, it often needs to be curated within a data warehouse.

Optimization 57

Optimization Strategy Data Warehouse Cost-Benefit 57

David Menninger's Analyst Perspectives

DECEMBER 29, 2022

Organizations conduct data analysis in many ways. The process can include multiple spreadsheets, applications, desktop tools, disparate data systems, data warehouses and analytics solutions. This creates difficulties for management to provide and maintain updated information across multiple departments.

Business Intelligence 196

Business Intelligence Analytics Data Warehouse Software 196

Cloudera

OCTOBER 4, 2023

A unique architecture to optimize for real-time data warehousing and business analytics: Cloudera Data Platform (CDP) offers Apache Kudu as part of our Data Hub cloud service, providing a consistent, dependable way to support the ingestion of data streams into our analytics environment, in real time, and at any scale.

Data Warehouse 83

Data Warehouse Experimentation Cost-Benefit Dashboards 83

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 89

Data Lake Data Warehouse Machine Learning Cost-Benefit 89

Analytics Vidhya

MARCH 17, 2022

This article was published as a part of the Data Science Blogathon. Machine learning and artificial intelligence, which are at the top of the list of data science capabilities, aren’t just buzzwords; many companies are keen to implement them.

Machine Learning 314

Machine Learning Data Science Publishing Analytics 314

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 88

Data Lake Data Warehouse Machine Learning Cost-Benefit 88

Cloudera

FEBRUARY 12, 2024

For data warehouse: create data warehouses through the Cloudera command line interface with the parameter “privateDNSZoneAKS”: set to”None.” ” For Liftie-based data services: the entitlement “LIFTIE_AKS_DISABLE_PRIVATE_DNS_ZONE” must be set.

Data Warehouse 52

Data Warehouse Machine Learning Data Lake Management 52

AWS Big Data

NOVEMBER 10, 2023

Amazon Redshift offers seamless integration with Apache Spark, allowing you to easily access your Redshift data on both Amazon Redshift provisioned clusters and Amazon Redshift Serverless. These tables are then joined with tables from the Enterprise Data Lake (EDL) at runtime. In his spare time, he enjoys reading and traveling.

Data Processing 89

Data Processing Data Lake Data Warehouse Optimization 89

DataRobot Blog

MARCH 8, 2023

Today, SAP and DataRobot announced a joint partnership to enable customers connect core SAP software, containing mission-critical business data, with the advanced Machine Learning capabilities of DataRobot to make more intelligent business predictions with advanced analytics.

Enterprise 105

Enterprise Experimentation Machine Learning Modeling 105

CIO Business Intelligence

APRIL 12, 2023

Real-time AI involves processing data for making decisions within a given time frame. Real-time AI brings together streaming data and machine learning algorithms to make fast and automated decisions; examples include recommendations, fraud detection, security monitoring, and chatbots. It isn’t easy.

Machine Learning 136

Machine Learning Cost-Benefit Data-driven Strategy 136

Smart Data Collective

OCTOBER 27, 2021

Snowflake provides the right balance between the cloud and data warehousing, especially when data warehouses like Teradata and Oracle are becoming too expensive for their users. It is also easy to get started with Snowflake as the typical complexity of data warehouses like Teradata and Oracle are hidden from the users. .

Interactive 115

Interactive Unstructured Data Analytics Data Warehouse 115

Cloudera

OCTOBER 13, 2020

In the beginning, CDP ran only on AWS with a set of services that supported a handful of use cases and workload types: CDP Data Warehouse: a kubernetes-based service that allows business analysts to deploy data warehouses with secure, self-service access to enterprise data.

Data Warehouse 90

Data Warehouse Machine Learning Visualization Data Lake 90

Octopai

APRIL 24, 2023

This new native integration enhances our data lineage solution by providing seamless integration with one of the most powerful cloud-based data warehouses, benefiting data teams and enabling support for a broader range of data lineage, discovery, and catalog.

Cost-Benefit 96

Cost-Benefit Data-driven Data Warehouse Data Governance 96

FineReport

MAY 6, 2020

Software Pemvisualisasi Data: excel, python, software profesional lainnya. Framework Big Data Processing: Hadoop, storm, spark. Data Warehous: SSIS, SSAS. Machine learning. Skill Data Mining: Matlab, R, Python. Seperti yang Anda ketahui, statistik adalah dasar analisis data. Data Warehouse.

Data mining 98

Data mining Data Warehouse Machine Learning Big Data 98

AWS Big Data

APRIL 29, 2024

The construction of big data applications based on open source software has become increasingly uncomplicated since the advent of projects like Data on EKS , an open source project from AWS to provide blueprints for building data and machine learning (ML) applications on Amazon Elastic Kubernetes Service (Amazon EKS).

Management 89

Management Big Data Metadata Data Warehouse 89