Analytics Vidhya

OCTOBER 10, 2022

This article was published as a part of the Data Science Blogathon. Introduction A key aspect of big data is data frames. However, Spark is more suited to handling scaled distributed data, whereas Pandas is not. Pandas and Spark are two of the most popular types. What […].

Data Science 395

Data Science Big Data Publishing Analytics 395

AWS Big Data

NOVEMBER 7, 2024

BladeBridge offers a comprehensive suite of tools that automate much of the complex conversion work, allowing organizations to quickly and reliably transition their data analytics capabilities to the scalable Amazon Redshift data warehouse. times better price performance than other cloud data warehouses.

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

Analytics Vidhya

SEPTEMBER 18, 2022

This article was published as a part of the Data Science Blogathon. Introduction Apache SQOOP is a tool designed to aid in the large-scale export and import of data into HDFS from structured data repositories. Relational databases, enterprise data warehouses, and NoSQL systems are all examples of data storage.

Data Warehouse 271

Data Warehouse Structured Data Data Science Publishing 271

CIO Business Intelligence

DECEMBER 11, 2024

This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. They must also select the data processing frameworks such as Spark, Beam or SQL-based processing and choose tools for ML.

Management 111

Management Data Governance Data Science Reporting 111

Smart Data Collective

NOVEMBER 18, 2020

Unfortunately, despite the growing interest in big data careers, many people don’t know how to pursue them properly. You should learn what a big data career looks like , which involves knowing the differences between different data processes. What is Data Science? Where to Use Data Science?

Data mining 144

Data mining Data Science Informatics Statistics 144

DataKitchen

APRIL 13, 2021

Piperr.io — Pre-built data pipelines across enterprise stakeholders, from IT to analytics, tech, data science and LoBs. Prefect Technologies — Open-source data engineering platform that builds, tests, and runs data workflows. Genie — Distributed big data orchestration service by Netflix.

Testing 304

Testing Machine Learning Consulting Data Science 304

DataKitchen

DECEMBER 7, 2021

Fail Fast, Learn Faster: Lessons in Data-Driven Leadership in an Age of Disruption, Big Data, and AI, by Randy Bean. This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. A distributed data mesh is a better choice. How did we get here?

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

CIO Business Intelligence

JUNE 14, 2023

Data and big data analytics are the lifeblood of any successful business. Getting the technology right can be challenging but building the right team with the right skills to undertake data initiatives can be even harder — a challenge reflected in the rising demand for big data and analytics skills and certifications.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

AWS Big Data

JANUARY 15, 2025

For container terminal operators, data-driven decision-making and efficient data sharing are vital to optimizing operations and boosting supply chain efficiency. Two use cases illustrate how this can be applied for business intelligence (BI) and data science applications, using AWS services such as Amazon Redshift and Amazon SageMaker.

IoT 111

IoT Machine Learning Metadata Data-driven 111

AWS Big Data

DECEMBER 4, 2024

SageMaker brings together widely adopted AWS ML and analytics capabilities—virtually all of the components you need for data exploration, preparation, and integration; petabyte-scale big data processing; fast SQL analytics; model development and training; governance; and generative AI development.

Data Analytics 105

Data Analytics Analytics Data Lake Data Quality 105

Data Science 101

NOVEMBER 7, 2019

Microsoft just held one of its largest conferences of the year, and a few major announcements were made which pertain to the cloud data science world. Azure Synapse Analytics can be seen as a merge of Azure SQL Data Warehouse and Azure Data Lake. Those are the big data science announcements of the week.

Data Science 106

Data Science Machine Learning Data Lake Visualization 106

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. Big data and data warehousing.

Technology 144

Technology Data Warehouse Big Data Machine Learning 144

AWS Big Data

NOVEMBER 22, 2024

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that you can use to analyze your data at scale. She has helped many customers build large-scale data warehouse solutions in the cloud and on premises. She is passionate about data analytics and data science.

Data Warehouse 105

Data Warehouse Recreation/Entertainment Cost-Benefit Data-driven 105

Alation

AUGUST 4, 2022

It’s been one decade since the “ Big Data Era ” began (and to much acclaim!). Analysts asked, What if we could manage massive volumes and varieties of data? Yet the question remains: How much value have organizations derived from big data? Big Data as an Enabler of Digital Transformation.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

Analytics Vidhya

JUNE 26, 2023

Introduction In today’s data-driven world, the role of data scientists has become indispensable. in data science to unravel the mysteries hidden within vast data sets? But what if I told you that you don’t need a Ph.D.

Data-driven 306

Data-driven Data Science Analytics Data mining 306

Jen Stirrup

MAY 5, 2020

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. How can you differentiate the different opportunities to store your data in Azure? Organizations need to recast storing their data.

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

Analytics Vidhya

SEPTEMBER 1, 2021

This article was published as a part of the Data Science Blogathon A data scientist’s ability to extract value from data is closely related to how well-developed a company’s data storage and processing infrastructure is.

Data Science 295

Data Science Publishing Modeling Analytics 295

CIO Business Intelligence

OCTOBER 13, 2023

The data architect also “provides a standard common business vocabulary, expresses strategic requirements, outlines high-level integrated designs to meet those requirements, and aligns with enterprise strategy and related business architecture,” according to DAMA International’s Data Management Body of Knowledge.

Data Architecture 132

Data Architecture Data Warehouse Statistics Visualization 132

AWS Big Data

OCTOBER 14, 2024

Enterprise data is brought into data lakes and data warehouses to carry out analytical, reporting, and data science use cases using AWS analytical services like Amazon Athena , Amazon Redshift , Amazon EMR , and so on. About the author Naidu Rongal i is a Big Data and ML engineer at Amazon.

Metadata 105

Metadata Data Lake Modeling Data Warehouse 105

Analytics Vidhya

JUNE 28, 2022

This article was published as a part of the Data Science Blogathon. “Preponderance data opens doorways to complex and Avant analytics.” ” Introduction to SQL Queries Data is the premium product of the 21st century.

Data Science 270

Data Science Publishing Enterprise Analytics 270

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

Analytics Vidhya

DECEMBER 23, 2022

This article was published as a part of the Data Science Blogathon. Source: [link] Introduction In today’s digital world, data is generated at a swift pace. Data in itself is not useful unless we present it in a meaningful way and derive insights that help in making key business decisions.

Visualization 271

Visualization Business Intelligence Data Science Publishing 271

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. This results in less joins between the metric data in fact tables, and the dimensions. So let’s dive in! OLTP vs OLAP.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

CIO Business Intelligence

JUNE 29, 2022

The recent announcement of the Microsoft Intelligent Data Platform makes that more obvious, though analytics is only one part of that new brand. Azure Data Factory. Azure Data Explorer. Azure Data Lake Analytics. Data warehouses are designed for questions you already know you want to ask about your data, again and again.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

IBM Big Data Hub

AUGUST 5, 2019

In a previous blog , I explained how data science capabilities, massive parallel processing (MPP). and usability improvements in data warehouse appliances can help the bottom line—and why old-fashioned architectures might not cut it. But what does that look like in practice?

Data Warehouse 59

Data Warehouse Data Science IT 59

CIO Business Intelligence

SEPTEMBER 14, 2023

These generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, as smaller businesses often don’t need to engineer for scale.

Analytics 135

Analytics Data Science Unstructured Data Data mining 135

CIO Business Intelligence

AUGUST 9, 2022

These generalists are often responsible for every step of the data process, from managing data to analyzing it. Dataquest says this is a good role for anyone looking to transition from data science to data engineering, as smaller businesses often don’t need to engineer for scale. Data engineer job description.

Analytics 131

Analytics Data Science Statistics Unstructured Data 131

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 116

Data Lake Data Warehouse Data-driven Optimization 116

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? This post will dive deeper into the nuances of each field.

Machine Learning 54

Machine Learning Data Science Statistics Deep Learning 54

AWS Big Data

NOVEMBER 8, 2023

This post was co-written with Rajiv Arora, Director of Data Science Platform at Gilead Life Sciences. Gilead Sciences, Inc. Amazon Redshift Serverless is a fully managed cloud data warehouse that allows you to seamlessly create your data warehouse with no infrastructure management required.

Data Lake 105

Data Lake Data Warehouse Cost-Benefit Optimization 105

CIO Business Intelligence

JUNE 23, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 98

Data Lake Data Warehouse Machine Learning Data-driven 98

datapine

MARCH 31, 2022

This could involve anything from learning SQL to buying some textbooks on data warehouses. BI developer skills encompass crafting and executing data-driven queries upon request as well as the ongoing technical development of a company’s BI platforms or solutions. Business Intelligence Job Roles. Yes, they exist.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 122

Data Lake Sales Data Warehouse Snapshot 122

Cloudera

JUNE 18, 2022

These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. In recent years, the term “data lakehouse” was coined to describe this architectural pattern of tabular analytics over data in the data lake.

Data Lake 94

Data Lake Data Warehouse Machine Learning Data-driven 94

CDW Research Hub

JULY 18, 2022

While many organizations understand the business need for a data and analytics cloud platform , few can quickly modernize their legacy data warehouse due to a lack of skills, resources, and data literacy. Overall data architecture and strategy. Cost reduction and best business practices.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87