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 Warehouse 59

Data Warehouse Data Lakes Hadoop Big Data 59

Analytics Vidhya

JUNE 22, 2022

Introduction In today’s data-driven age, an enormous amount of data is getting generated every day from various sources such as social media, e-commerce websites, stock exchanges, transaction processing systems, emails, medical records, etc. This data is a combination of structured, unstructured, and semi-structured […].

Data Science 369

Data Science Analytics Analytics Data Warehouse 369

Analytics Vidhya

FEBRUARY 17, 2023

Through these webinars, you’ll gain hands-on experience, deepen your understanding […] The post Join DataHour Sessions With Industry Experts appeared first on Analytics Vidhya.

Analytics 319

Analytics Analytics Data Pipeline Data Warehouse 319

IBM Journey to AI blog

APRIL 24, 2023

Data is reported from one central repository, enabling management to draw more meaningful business insights and make faster, better decisions. By running reports on historical data, a data warehouse can clarify what systems and processes are working and what methods need improvement.

Data Warehouse 112

Data Warehouse Data Lakes Database Big Data 112

Analytics Vidhya

MARCH 31, 2023

Publishers can publish […] The post Complete Guide to Pub/Sub in Redis appeared first on Analytics Vidhya. These senders are called Publishers, responsible for publishing these messages, and the receivers are called Subscribers who subscribe to these Publishers to receive their notifications.

Analytics 328

Analytics Analytics Data Warehouse Data Engineering 328

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. The post How Will The Cloud Impact Data Warehousing Technologies?

Data Warehouse 144

Data Warehouse Big Data Big Data Big Data Analytics 144

Analytics Vidhya

APRIL 3, 2023

Real-time dashboards such as GCP provide strong data visualization and actionable information for decision-makers. Nevertheless, setting up a streaming data pipeline to power such dashboards may […] The post Data Engineering for Streaming Data on GCP appeared first on Analytics Vidhya.

Data Engineering 319

Data Engineering Data Engineering Data Engineer Data Engineering 319

Analytics Vidhya

DECEMBER 31, 2022

The post How to Encrypt and Decrypt the Data in PySpark? appeared first on Analytics Vidhya. To access services, we need to share essential details like email IDs, phone numbers, social security numbers, etc. These details can get leaked if the […].

Data Science 317

Data Science Analytics Analytics Data Warehouse 317

Analytics Vidhya

FEBRUARY 6, 2023

To make these processes efficient, data pipelines are necessary. Data engineers specialize in building and maintaining these data pipelines that underpin the analytics ecosystem. In this blog, we will […] The post How to Implement a Data Pipeline Using Amazon Web Services?

Data Pipeline 271

Data Pipeline Data Engineering Data Engineering Data Engineer 271

phData

FEBRUARY 21, 2025

In this post, we will be particularly interested in the impact that cloud computing left on the modern data warehouse. We will explore the different options for data warehousing and how you can leverage this information to make the right decisions for your organization. What is The Cloud?

Data Warehouse 52

Data Warehouse Cloud Data ETL Cloud Computing 52

Analytics Vidhya

DECEMBER 26, 2022

It involves extracting the operational data from various sources, transforming it into a format suitable for business needs, and loading it into data storage systems. The post Crafting Serverless ETL Pipeline Using AWS Glue and PySpark appeared first on Analytics Vidhya. Traditionally, ETL processes are […].

ETL 306

ETL AWS Data Engineering Data Engineering 306

Analytics Vidhya

DECEMBER 23, 2022

Data in itself is not useful unless we present it in a meaningful way and derive insights that help in making key business decisions. The post Visualize Your Data With Google Looker Studio appeared first on Analytics Vidhya. Business Intelligence (BI) tools serve the […].

Business Intelligence 271

Business Intelligence Business Intelligence Data Science Analytics 271

Analytics Vidhya

FEBRUARY 4, 2023

The transformation process occurs outside the target, a separate processing tool or […] The post Unlock the True Potential of Your Data with ETL and ELT Pipeline appeared first on Analytics Vidhya.

ETL 298

ETL Analytics Analytics Data Warehouse 298

Analytics Vidhya

FEBRUARY 20, 2023

Azure data factory helps organizations across the globe in making critical business decisions by collecting data from various sources such as e-commerce websites, supply chains, logistics, […] The post Most Frequently Asked Azure Data Factory Interview Questions appeared first on Analytics Vidhya.

Azure 283

Azure ETL Analytics Analytics 283

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.

Analytics 72

Analytics Analytics Big Data Analytics Big Data Analytics 72

Smart Data Collective

OCTOBER 13, 2021

If we talk about Big Data, data visualization is crucial to more successfully drive high-level decision making. Big Data analytics has immense potential to help companies in decision making and position the company for a realistic future. There is little use for data analytics without the right visualization tool.

Data Visualization 145

Data Visualization Big Data Big Data Predictive Analytics 145

Analytics Vidhya

FEBRUARY 25, 2023

Data lakes provide a way to store and process large amounts of raw data in its original format, […] The post Setting up Data Lake on GCP using Cloud Storage and BigQuery appeared first on Analytics Vidhya.

Data Lakes 178

Data Lakes Analytics Analytics Data Warehouse 178

phData

MAY 25, 2023

How to Optimize Power BI and Snowflake for Advanced Analytics Spencer Baucke May 25, 2023 The world of business intelligence and data modernization has never been more competitive than it is today. Much of what is discussed in this guide will assume some level of analytics strategy has been considered and/or defined. No problem!

Power BI 84

Power BI Analytics Analytics Azure 84

ODSC - Open Data Science

JUNE 22, 2023

These are called data lakes. What Are Data Lakes? Unlike databases and data warehouses, data lakes can store data in raw and unstructured forms. This feature is important because it allows data lakes to hold a larger amount of data and store it faster.

Data Lakes 98

Data Lakes Data Warehouse Data Science Database 98

Dataconomy

SEPTEMBER 27, 2023

The Microsoft Certified Solutions Associate and Microsoft Certified Solutions Expert certifications cover a wide range of topics related to Microsoft’s technology suite, including Windows operating systems, Azure cloud computing, Office productivity software, Visual Studio programming tools, and SQL Server databases.

Database Administration 113

Database Administration Database Azure Cloud Computing 113

Pickl AI

OCTOBER 6, 2024

It is a crucial data integration process that involves moving data from multiple sources into a destination system, typically a data warehouse. This process enables organisations to consolidate their data for analysis and reporting, facilitating better decision-making. ETL stands for Extract, Transform, and Load.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

IBM Journey to AI blog

DECEMBER 7, 2023

Online analytical processing (OLAP) database systems and artificial intelligence (AI) complement each other and can help enhance data analysis and decision-making when used in tandem. Early OLAP systems were separate, specialized databases with unique data storage structures and query languages.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. It is known to have benefits in handling data due to its robustness, speed, and scalability. Data ingestion/integration services. Data orchestration tools.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

Dataversity

NOVEMBER 25, 2022

At the same time, many forward-thinking businesses, from startups to large corporations, have implemented a modern cloud analytics stack to use data more efficiently. The post How a Modern Cloud Analytics Stack Can Optimize the Value of Your Data appeared first on DATAVERSITY.

Analytics 52

Analytics Analytics Data Warehouse Cloud Computing 52

Alation

DECEMBER 14, 2021

To that end, AWS is making inroads into the analytics and machine learning space. Customer stories shed light on the cloud benefits for analytics. They do this by leveraging this single platform, which integrates with thousands of partners and supports 475 instances to unify data across an enterprise. In Conclusion.

AWS 52

AWS Data Lakes Data Warehouse Machine Learning 52

Mlearning.ai

FEBRUARY 16, 2023

Today, companies are facing a continual need to store tremendous volumes of data. The demand for information repositories enabling business intelligence and analytics is growing exponentially, giving birth to cloud solutions. Snowflake data warehouses deliver greater capacity without the need for any additional equipment.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

Alation

JULY 13, 2021

This recent cloud migration applies to all who use data. We have seen the COVID-19 pandemic accelerate the timetable of cloud data migration , as companies evolve from the traditional data warehouse to a data cloud, which can host a cloud computing environment. Fern Halper, Ph.D.

Cloud Data 52

Cloud Data Data Governance Data Mining Data Warehouse 52

Precisely

MARCH 10, 2023

Accurate physical addresses play a vital role in most business analytics. This capability opens the door to a wide array of data analytics applications. The Rise of Cloud Analytics Data analytics has advanced rapidly over the past decade. Consequently, there is a growing demand for scalable analytics.

Analytics 59

Analytics Analytics Data Warehouse Big Data 59

IBM Journey to AI blog

SEPTEMBER 26, 2023

States’ existing investments in modernizing and enhancing ancillary supportive technologies (such as document management, web portals, mobile applications, data warehouses and location services) could negate the need for certain system requirements as part of the child support system modernization initiative.

Data Warehouse 112

Data Warehouse Cloud Computing Cloud Data Analytics 112

Pickl AI

NOVEMBER 4, 2024

Data Engineering is designing, constructing, and managing systems that enable data collection, storage, and analysis. It involves developing data pipelines that efficiently transport data from various sources to storage solutions and analytical tools. ETL is vital for ensuring data quality and integrity.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

IBM Journey to AI blog

JULY 31, 2023

Before the internet and cloud computing , and before smartphones and mobile apps, banks were shuttling payments through massive electronic settlement gateways and operating mainframes as systems of record. Complex analytical queries atop huge datasets on the mainframe can eat up compute budgets and take hours or days to run.

Analytics 64

Analytics Analytics Data Warehouse Cloud Computing 64

Precisely

JANUARY 25, 2024

Many organizations adopt a long-term approach, leveraging the relative strengths of both mainframe and cloud systems. This integrated strategy keeps a wide range of IT options open, blending the reliability of mainframes with the innovation of cloud computing. Let’s examine each of these patterns in greater detail.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

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? Answer : Polybase helps optimize data ingestion into PDW and supports T-SQL.

Azure 52

Azure Data Engineering Data Engineering Data Engineer 52

phData

NOVEMBER 1, 2023

The Snowflake Data Cloud offers a scalable, cloud-native data warehouse that provides the flexibility, performance, and ease of use needed to meet the demands of modern businesses. Conclusion Snowflake has truly revolutionized the way modern businesses handle their data processing and analytics needs.

Data Warehouse 52

Data Warehouse SQL Database Cloud Computing 52

IBM Journey to AI blog

JULY 6, 2023

It uses advanced tools to look at raw data, gather a data set, process it, and develop insights to create meaning. Areas making up the data science field include mining, statistics, data analytics, data modeling, machine learning modeling and programming. appeared first on IBM Blog.

Machine Learning 70

Machine Learning Machine Learning Data Science Big Data 70

Dataconomy

FEBRUARY 23, 2023

Collecting, storing, and processing large datasets Data engineers are also responsible for collecting, storing, and processing large volumes of data. This involves working with various data storage technologies, such as databases and data warehouses, and ensuring that the data is easily accessible and can be analyzed efficiently.

Big Data 91

Big Data Big Data Data Engineering Data Engineering 91

Pickl AI

DECEMBER 10, 2024

Summary: Oracle’s Exalytics, Exalogic, and Exadata transform enterprise IT with optimised analytics, middleware, and database systems. AI, hybrid cloud, and advanced analytics empower businesses to achieve operational excellence and drive digital transformation.

Database 52

Database Analytics Analytics Business Intelligence 52