AWS Machine Learning Blog

OCTOBER 24, 2024

The analyst can easily pull in the data they need, use natural language to clean up and fill any missing data, and finally build and deploy a machine learning model that can accurately predict the loan status as an output, all without needing to become a machine learning expert to do so. Database name : Enter dev.

Data Warehouse 122

Data Warehouse Machine Learning Machine Learning Cloud Data 122

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.

Data Warehouse 141

Data Warehouse Big Data Big Data Business Intelligence 141

Smart Data Collective

APRIL 15, 2021

Business Intelligence is the practice of collecting and analyzing data and transforming it into useful, actionable information. In order to make good business decisions, leaders need accurate insights into both the market and day-to-day operations. Set Up Data Integration. What kinds of BI tools are available ?

Business Intelligence 97

Business Intelligence Business Intelligence Analytics Analytics 97

Pickl AI

DECEMBER 15, 2024

Summary : This guide provides an in-depth look at the top data warehouse interview questions and answers essential for candidates in 2025. Covering key concepts, techniques, and best practices, it equips you with the knowledge needed to excel in interviews and demonstrates your expertise in data warehousing.

Data Warehouse 52

Data Warehouse ETL Database Data Quality 52

Smart Data Collective

FEBRUARY 20, 2022

Since databases store companies’ valuable digital assets and corporate secrets, they are on the receiving end of quite a few cyber-attack vectors these days. How can database activity monitoring (DAM) tools help avoid these threats? What are the ties between DAM and data loss prevention (DLP) systems? How do DAM solutions work?

Database 127

Database Machine Learning Machine Learning Data Warehouse 127

Smart Data Collective

OCTOBER 27, 2021

An interactive analytics application gives users the ability to run complex queries across complex data landscapes in real-time: thus, the basis of its appeal. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights. Druid is a real-time analytics database from Apache.

Analytics 125

Analytics Analytics Data Warehouse Business Intelligence 125

Women in Big Data

NOVEMBER 27, 2024

A data warehouse is a centralized repository designed to store and manage vast amounts of structured and semi-structured data from multiple sources, facilitating efficient reporting and analysis. Begin by determining your data volume, variety, and the performance expectations for querying and reporting.

Data Warehouse 59

Data Warehouse Big Data Big Data Azure 59

Dataconomy

MAY 10, 2023

Open source business intelligence software is a game-changer in the world of data analysis and decision-making. It has revolutionized the way businesses approach data analytics by providing cost-effective and customizable solutions that are tailored to specific business needs.

Business Intelligence 178

Business Intelligence Business Intelligence Power BI Data Analysis 178

IBM Journey to AI blog

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

Data Science Blog

MAY 15, 2023

tl;dr Ein Data Lakehouse ist eine moderne Datenarchitektur, die die Vorteile eines Data Lake und eines Data Warehouse kombiniert. Organisationen können je nach ihren spezifischen Bedürfnissen und Anforderungen zwischen einem Data Warehouse und einem Data Lakehouse wählen.

Data Warehouse 147

Data Warehouse Data Lakes Azure AWS 147

Smart Data Collective

JULY 22, 2019

Big or small, every business needs good tools to analyze data and develop the most suitable business strategy based on the information they get. Business intelligence tools are means that help companies get insights from their data and get a better understanding of what directions and trends to follow.

Business Intelligence 85

Business Intelligence Business Intelligence Power BI Tableau 85

ODSC - Open Data Science

SEPTEMBER 27, 2023

In this article, we will delve into the concept of data lakes, explore their differences from data warehouses and relational databases, and discuss the significance of data version control in the context of large-scale data management. Before we address the questions, ‘ What is data version control ?’

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 52

IBM Journey to AI blog

MARCH 14, 2024

The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage. Also, traditional database management tasks, including backups, upgrades and routine maintenance drain valuable time and resources, hindering innovation.

AWS 93

AWS Database AI AI 93

Data Science Dojo

FEBRUARY 1, 2023

Azure Synapse provides a unified platform to ingest, explore, prepare, transform, manage, and serve data for BI (Business Intelligence) and machine learning needs. DWUs (Data Warehouse Units) can customize resources and optimize performance and costs.

Azure 195

Azure SQL Analytics Analytics 195

Dataconomy

MARCH 24, 2023

In today’s fast-paced business landscape, companies need to stay ahead of the curve to remain competitive. Business intelligence (BI) has emerged as a key solution to help companies gain insights into their operations and market trends. What is business intelligence?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

Dataconomy

MARCH 24, 2023

In today’s fast-paced business landscape, companies need to stay ahead of the curve to remain competitive. Business intelligence (BI) has emerged as a key solution to help companies gain insights into their operations and market trends. What is business intelligence?

Business Intelligence 70

Business Intelligence Business Intelligence Data Analysis Data Analysis 70

phData

SEPTEMBER 8, 2023

Business intelligence (BI) has become the cornerstone of decision making for businesses, leading organizations to constantly seek innovative solutions to harness the power of their data. Snowflake Data Cloud, a cloud-native data platform, has emerged as a leading choice for business intelligence (BI) initiatives.

Business Intelligence 59

Business Intelligence Business Intelligence Database Data Warehouse 59

Dataversity

DECEMBER 15, 2021

The abilities of an organization towards capturing, storing, and analyzing data; searching, sharing, transferring, visualizing, querying, and updating data; and meeting compliance and regulations are mandatory for any sustainable organization. For example, most data warehouses […].

Data Warehouse 98

Data Warehouse Data Lakes Database Business Intelligence 98

Smart Data Collective

SEPTEMBER 8, 2021

The ETL process is defined as the movement of data from its source to destination storage (typically a Data Warehouse) for future use in reports and analyzes. The data is initially extracted from a vast array of sources before transforming and converting it to a specific format based on business requirements.

ETL 107

ETL Hadoop Data Warehouse Data Pipeline 107

Smart Data Collective

JUNE 16, 2022

Online analytical processing is a computer method that enables users to retrieve and query data rapidly and carefully in order to study it from a variety of angles. Trend analysis, financial reporting, and sales forecasting are frequently aided by OLAP business intelligence queries. ( see more ).

Analytics 137

Analytics Analytics Data Scientist Data Warehouse 137

Alation

MARCH 29, 2022

Business intelligence has a long history. Today, the term describes that same activity, but on a much larger scale, as organizations race to collect, analyze, and act on data first. With remote and hybrid work on the rise, the ability to locate and leverage data and expertise — wherever it resides — is more critical than ever.

Business Intelligence 96

Business Intelligence Business Intelligence Data Silos Citizen Data Scientist 96

AWS Machine Learning Blog

DECEMBER 29, 2022

Many of the RStudio on SageMaker users are also users of Amazon Redshift , a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools.

AWS 134

AWS Machine Learning Machine Learning Natural Language Processing 134

ODSC - Open Data Science

FEBRUARY 24, 2023

There are many well-known libraries and platforms for data analysis such as Pandas and Tableau, in addition to analytical databases like ClickHouse, MariaDB, Apache Druid, Apache Pinot, Google BigQuery, Amazon RedShift, etc. With Great Expectations , data teams can express what they “expect” from their data using simple assertions.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Smart Data Collective

JULY 9, 2023

ETL (Extract, Transform, Load) is a crucial process in the world of data analytics and business intelligence. In this article, we will explore the significance of ETL and how it plays a vital role in enabling effective decision making within businesses. Let’s break down each step: 1.

ETL 97

ETL Data Quality Data Warehouse Database 97

IBM Journey to AI blog

APRIL 8, 2024

The new Amazon Relational Database Service (Amazon RDS) for Db2 offering allows customers to migrate their existing, self-managed Db2 databases to the cloud and accelerate strategic modernization initiatives. Answer : Yes, Amazon RDS for Db2 can support analytics workloads, but it is not a data warehouse. Amazon RDS

AWS 87

AWS Database Data Warehouse Analytics 87

IBM Journey to AI blog

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Data Warehouse 58

Data Warehouse Data Engineering Data Engineer Data Engineering 58

Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. If it’s not done right away, then later.

Database 108

Database Data Visualization Data Mining Data Mining 108

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

IBM Journey to AI blog

MAY 9, 2023

Watsonx.data will allow users to access their data through a single point of entry and run multiple fit-for-purpose query engines across IT environments. Through workload optimization an organization can reduce data warehouse costs by up to 50 percent by augmenting with this solution. [1]

Data Warehouse 92

Data Warehouse AWS AI AI 92

ODSC - Open Data Science

FEBRUARY 8, 2023

Common databases appear unable to cope with the immense increase in data volumes. This is where the BigQuery data warehouse comes into play. BigQuery operation principles Business intelligence projects presume collecting information from different sources into one database.

Database 97

Database Business Intelligence Business Intelligence Big Data 97

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation.

Data Warehouse 88

Data Warehouse Azure SQL ETL 88

Dataconomy

SEPTEMBER 4, 2023

Data models help visualize and organize data, processing applications handle large datasets efficiently, and analytics models aid in understanding complex data sets, laying the foundation for business intelligence. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

IBM Journey to AI blog

SEPTEMBER 11, 2023

Don Haderle, a retired IBM Fellow and considered to be the “father of Db2,” viewed 1988 as a seminal point in its development as D B2 version 2 proved it was viable for online transactional processing (OLTP)—the lifeblood of business computing at the time. Db2 (LUW) was born in 1993, and 2023 marks its 30th anniversary.

Database 101

Database SQL Data Warehouse Machine Learning 101

ODSC - Open Data Science

JUNE 12, 2023

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. The Datamart’s data is usually stored in databases containing a moving frame required for data analysis, not the full history of data.

Power BI 52

Power BI Data Warehouse ETL Data Preparation 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

IBM Journey to AI blog

OCTOBER 22, 2024

Data must be combined and harmonized from multiple sources into a unified, coherent format before being used with AI models. This process is known as data integration , one of the key components to improving the usability of data for AI and other use cases, such as business intelligence (BI) and analytics.

Data Silos 102

Data Silos Data Pipeline DataOps Business Intelligence 102