Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. In this article, we’ll focus on a data lake vs. data warehouse.

Data Lakes 59

Data Lakes Data Warehouse Hadoop Big Data 59

Flipboard

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Text, images, audio, and videos are common examples of unstructured data. Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly.

AWS 165

AWS ML ML Analytics 165

Data Science Dojo

JULY 6, 2023

Google BigQuery: Google BigQuery is a serverless, cloud-based data warehouse designed for big data analytics. It offers scalable storage and compute resources, enabling data engineers to process large datasets efficiently. It supports batch processing and is widely used for data-intensive tasks.

Data Engineering 195

Data Engineering Data Engineering Data Engineer Data Engineering 195

Alation

FEBRUARY 20, 2020

Architecturally the introduction of Hadoop, a file system designed to store massive amounts of data, radically affected the cost model of data. Organizationally the innovation of self-service analytics, pioneered by Tableau and Qlik, fundamentally transformed the user model for data analysis.

Data Lakes 52

Data Lakes Hadoop Tableau Big Data 52

IBM Journey to AI blog

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 94

Data Science Analytics Analytics Data Scientist 94

AWS Machine Learning Blog

OCTOBER 20, 2023

Data and governance foundations – This function uses a data mesh architecture for setting up and operating the data lake, central feature store, and data governance foundations to enable fine-grained data access. This framework considers multiple personas and services to govern the ML lifecycle at scale.

ML 135

ML ML AWS Data Lakes 135

Precisely

OCTOBER 16, 2023

Rapid advancements in digital technologies are transforming cloud-based computing and cloud analytics. Big data analytics, IoT, AI, and machine learning are revolutionizing the way businesses create value and competitive advantage. In a connected mainframe/cloud environment, data is often diverse and fragmented.

Analytics 72

Analytics Analytics Big Data Analytics Big Data Analytics 72

Dataconomy

MAY 26, 2025

As businesses increasingly depend on big data to tailor their strategies and enhance decision-making, the role of these engineers becomes more crucial. They not only manage extensive data architectures but also pave the way for effective data analytics and innovative solutions. What is a big data engineer?

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

Tableau

MARCH 10, 2022

Salesforce CDP creates holistic customer views by pulling data from internal and external databases and building unified customer profiles. From there, Tableau CRM provides actionable insights and AI-driven analytics empowering people to make the best decisions for their customers. . Getting started with CDP Direct.

Tableau 98

Tableau Data Lakes Analytics Analytics 98

Tableau

MARCH 10, 2022

Salesforce CDP creates holistic customer views by pulling data from internal and external databases and building unified customer profiles. From there, Tableau CRM provides actionable insights and AI-driven analytics empowering people to make the best decisions for their customers. . Getting started with CDP Direct.

Tableau 98

Tableau Data Lakes Analytics Analytics 98

AWS Machine Learning Blog

FEBRUARY 21, 2025

Thats why we use advanced technology and data analytics to streamline every step of the homeownership experience, from application to closing. Apache HBase was employed to offer real-time key-based access to data. HBase is employed to offer real-time key-based access to data. Analytic data is stored in Amazon Redshift.

Data Science 85

Data Science AWS Hadoop Data Scientist 85

Tableau

APRIL 18, 2022

Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. . At Tableau, we believe that the best decisions are made when everyone is empowered to put data at the center of every conversation.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

Instead of centralizing data stores, data fabrics establish a federated environment and use artificial intelligence and metadata automation to intelligently secure data management. . At Tableau, we believe that the best decisions are made when everyone is empowered to put data at the center of every conversation.

Tableau 98

Tableau Data Quality Analytics Analytics 98

AWS Machine Learning Blog

AUGUST 21, 2023

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface.

AWS 98

AWS Data Lakes Clustering Data Preparation 98

ODSC - Open Data Science

MAY 8, 2023

Article on Azure ML by Bethany Jepchumba and Josh Ndemenge of Microsoft In this article, I will cover how you can train a model using Notebooks in Azure Machine Learning Studio. At the end of this article, you will learn how to use Pytorch pretrained DenseNet 201 model to classify different animals into 48 distinct categories.

Azure 52

Azure ML ML Data Modeling 52

Tableau

MAY 11, 2022

At Tableau, we believe data is most valuable when everyone in an organization can use it to make better, data-driven decisions. Data refresh failure detection that flags the issue to data users for mitigation and downstream consumers. This eliminates the need to set up an index schedule or configure connectivity.

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

Tableau

MAY 11, 2022

At Tableau, we believe data is most valuable when everyone in an organization can use it to make better, data-driven decisions. Data refresh failure detection that flags the issue to data users for mitigation and downstream consumers. This eliminates the need to set up an index schedule or configure connectivity.

Tableau 98

Tableau Data Warehouse Database Data Analyst 98

ODSC - Open Data Science

MARCH 23, 2023

Real-time Analytics & Built-in Machine Learning Models with a Single Database Akmal Chaudhri, Senior Technical Evangelist at SingleStore, explores the importance of delivering real-time experiences in today’s big data industry and how data models and algorithms rely on powerful and versatile data infrastructure.

Data Science 52

Data Science Data Lakes Machine Learning Machine Learning 52

Women in Big Data

NOVEMBER 27, 2024

By maintaining historical data from disparate locations, a data warehouse creates a foundation for trend analysis and strategic decision-making. Finally, conduct a proof of concept to assess how the data warehouse meets requirements. Featuring a robust architecture, it powers efficient data storage, processing, and querying.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

Alation

FEBRUARY 20, 2020

Organizations who are so successful in their adoption of self-service analytics, that their own business intelligence (BI) evangelists worry that they’ve created an analytics “wild west.” When they see a data catalog for the first time, they’re thrilled that a product exists that can govern the west and increase analyst productivity.

Data Lakes 52

Data Lakes Analytics Analytics Business Intelligence 52

Pickl AI

JANUARY 28, 2025

Research indicates that companies utilizing advanced analytics are 5 times more likely to make faster decisions than their competitors. Key Components of Business Intelligence Architecture Business Intelligence (BI) architecture is a structured framework that enables organizations to gather, analyze, and present data effectively.

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

Pickl AI

NOVEMBER 4, 2024

Summary: The fundamentals of Data Engineering encompass essential practices like data modelling, warehousing, pipelines, and integration. Understanding these concepts enables professionals to build robust systems that facilitate effective data management and insightful analysis. What is Data Engineering?

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Tableau

DECEMBER 7, 2022

Now powered by Tableau, Genie brings that trusted, up-to-the-moment customer data to life by layering on visual, explorable, and actionable analytics and insights. . Built-in connectors bring in data from every single channel. Go from a data set to an intuitive dashboard in Tableau with a single click of a button.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Tableau

DECEMBER 7, 2022

Now powered by Tableau, Genie brings that trusted, up-to-the-moment customer data to life by layering on visual, explorable, and actionable analytics and insights. . Built-in connectors bring in data from every single channel. Go from a data set to an intuitive dashboard in Tableau with a single click of a button.

Tableau 98

Tableau Data Warehouse Data Pipeline Data Visualization 98

Precisely

MARCH 27, 2023

Transforming Go-to-Market After years of acquiring and integrating smaller companies, a $37 billion multinational manufacturer of confectionery, pet food, and other food products was struggling with complex and largely disparate processes, systems, and data models that needed to be normalized.

Data Quality 52

Data Quality Data Lakes Data Governance Data Modeling 52

AWS Machine Learning Blog

SEPTEMBER 5, 2023

The portal combines these predictive alerts with other insights we derive from our AWS-based data lake in order to give our dealers more clarity into equipment health across their entire client base. About the Authors Ravi Patankar is a technical leader for IoT related analytics at Carrier’s Residential HVAC Unit.

AWS 123

AWS ML ML Machine Learning 123

IBM Journey to AI blog

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

ODSC - Open Data Science

NOVEMBER 19, 2024

ODSC West 2024 showcased a wide range of talks and workshops from leading data science, AI, and machine learning experts. This blog highlights some of the most impactful AI slides from the world’s best data science instructors, focusing on cutting-edge advancements in AI, data modeling, and deployment strategies.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

Tableau

OCTOBER 8, 2024

Tableau Next is a reimagined analytics experience: an open, composable, enterprise-grade data and analytics platform built on the Salesforce Platform and deeply integrated with Agentforce, a suite of customizable AI agents and tools. What is Tableau Next and why now?

Tableau 52

Tableau Analytics Analytics Data Lakes 52

Tableau

OCTOBER 8, 2024

Tableau Einstein is a reimagined analytics experience: an open, composable, enterprise-grade data and analytics platform built on the Salesforce Platform and deeply integrated with Agentforce, a suite of customizable AI agents and tools. What is Tableau Einstein and why now?

Tableau 52

Tableau Analytics Analytics Data Lakes 52

ODSC - Open Data Science

JUNE 12, 2023

The Datamarts capability opens endless possibilities for organizations to achieve their data analytics goals on the Power BI platform. They all agree that a Datamart is a subject-oriented subset of a data warehouse focusing on a particular business unit, department, subject area, or business functionality. What is a Datamart?

Power BI 52

Power BI Data Warehouse ETL Data Preparation 52

phData

MAY 13, 2024

There are many challenges to overcome when doing this, and understanding them and choosing the right solutions is critical to the ultimate success and enablement of better decision-making using your ERP data. Additionally, change data markers are not available for many of these tables.

Database 52

Database Analytics Analytics Machine Learning 52

phData

SEPTEMBER 26, 2023

Sources The sources involved could influence or determine the options available for the data ingestion tool(s). These could include other databases, data lakes, SaaS applications (e.g. Data flows from the current data platform to the destination. Below are a few of the items that need to be taken into account.

SQL 52

SQL Database ETL Data Models 52

Pickl AI

APRIL 6, 2023

Data Engineering is one of the most productive job roles today because it imbibes both the skills required for software engineering and programming and advanced analytics needed by Data Scientists. How to Become an Azure Data Engineer? Data Warehousing concepts and knowledge should be strong. What is Polybase?

Azure 52

Azure Data Engineering Data Engineering Data Engineer 52

DagsHub

NOVEMBER 11, 2024

In this article, we’ll explore how AI can transform unstructured data into actionable intelligence, empowering you to make informed decisions, enhance customer experiences, and stay ahead of the competition. What is Unstructured Data? Sensor Data Sensor data can often be semi-structured rather than fully unstructured.

AI 52

AI AI Data Lakes Database 52

IBM Journey to AI blog

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools.

AI 88

AI AI Data Warehouse ML 88

Alation

FEBRUARY 13, 2020

Just as you need data about finances for effective financial management, you need data about data (metadata) for effective data management. You can’t manage data without metadata. But data catalogs do much more. Figure 1 shows a logical data model that represents typical metadata content of a data catalog.

Data Lakes 52

Data Lakes Data Governance Data Science Data Analyst 52