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

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. Schema Enforcement: Data warehouses use a “schema-on-write” approach.

Data Lakes 98

Data Lakes Data Warehouse Database Big Data 98

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

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. It involves drilling down into data to identify the root causes of specific outcomes.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Dataconomy

MAY 26, 2025

Aggregation of data: Compiling relevant business data from various sources. Data cleansing and integration: Ensuring data quality through processes that contribute to a centralized data repository (data warehouse or data mart).

Analytics 91

Analytics Analytics Data Analysis Data Analysis 91

AWS Machine Learning Blog

APRIL 3, 2025

Lambda enables serverless, event-driven data processing tasks, allowing for real-time transformations and calculations as data arrives. Step Functions complements this by orchestrating complex workflows, coordinating multiple Lambda functions, and managing error handling for sophisticated data processing pipelines.

AWS 84

AWS Data Governance Data Silos SQL 84

Pickl AI

MARCH 19, 2025

Apache Kafka Apache Kafka is a distributed event streaming platform used for real-time data processing. It helps data engineers collect, store, and process streams of records in a fault-tolerant way, making it crucial for building reliable data pipelines.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

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 98

Data Warehouse Azure SQL ETL 98

ODSC - Open Data Science

APRIL 25, 2025

Unfortunately, the current landscape of our consuming systems, especially business intelligence tools, just wont work withAPIs. The two most prominent implementations are dbt Model Contracts , and the Open Data Contract Standard (ODCS, not to be confused withODSC.

Data Engineering 52

Data Engineering Data Engineer Data Engineering Data Engineering 52

Dataconomy

APRIL 27, 2023

What is an online transaction processing database: Indexed data sets are used for rapid querying in OLTP systems Regular & incremental backups for data safety Frequent backups are necessary to ensure that data is protected in the event of a system failure or other issue.

Database 159

Database Data Scientist Data Mining Data Mining 159

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

Pickl AI

JULY 25, 2024

Must Read Blogs: Exploring the Power of Data Warehouse Functionality. Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. Explore: How Business Intelligence helps in Decision Making.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

phData

JUNE 5, 2025

In the fast-moving world of data, the Snowflake AI Data Cloud has established itself as an essential part of the Modern Data Stack. Through its versatile platform, organizations can build efficient data warehouses and harness the power of data monetization via Secure Data Shares, accessible through the Snowflake Marketplace.

Database 52

Database Azure AWS SQL 52

Smart Data Collective

FEBRUARY 20, 2022

On the one hand, the use of agents allows you to actively monitor and respond to events. On the other hand, many companies are skeptical about third-party intervention in their business processes and limit the use of DAM to logging only. There are different opinions. DAM deployment best practices. Let’s get to the bottom of this.

Database 130

Database Machine Learning Machine Learning Data Warehouse 130

ODSC - Open Data Science

FEBRUARY 6, 2024

Google BigQuery When it comes to cloud data warehouses, Snowflake, Amazon Redshift, and Google BigQuery are often at the forefront of discussions. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences. Interested in attending an ODSC event?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

phData

SEPTEMBER 5, 2023

Google Analytics 4 (GA4) is a powerful tool for collecting and analyzing website and app data that many businesses rely heavily on to make informed business decisions. By the end of this tutorial, you’ll have a seamless pipeline that fetches and syncs your GA4 raw events data to Snowflake efficiently.

Azure 52

Azure Analytics Analytics Data Pipeline 52

IBM Journey to AI blog

OCTOBER 16, 2023

Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data. In addition to natural language, models are trained on various modalities, such as code, time-series, tabular, geospatial and IT events data.

AI 88

AI AI Data Warehouse ML 88

ODSC - Open Data Science

JANUARY 30, 2024

This involves extracting data from various sources, transforming it into a usable format, and loading it into data warehouses or other storage systems. Think of it as building plumbing for data to flow smoothly throughout the organization. Interested in attending an ODSC event?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Pickl AI

FEBRUARY 23, 2025

Statistics : A survey by Databricks revealed that 80% of Spark users reported improved performance in their data processing tasks compared to traditional systems. Google Cloud BigQuery Google Cloud BigQuery is a fully-managed enterprise data warehouse that enables super-fast SQL queries using the processing power of Googles infrastructure.

Big Data 52

Big Data Big Data Apache Hadoop Apache Kafka 52

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

IBM Journey to AI blog

SEPTEMBER 19, 2023

Data analytics is a task that resides under the data science umbrella and is done to query, interpret and visualize datasets. Data scientists will often perform data analysis tasks to understand a dataset or evaluate outcomes. Diagnostic analytics: Diagnostic analytics helps pinpoint the reason an event occurred.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

phData

DECEMBER 12, 2023

A complete view of the fan, rather than pieces of information spread across various departments, means less guesswork and more data insights. Step 2: Analyze the Data Once you have centralized your data, use a business intelligence tool like Sigma Computing , Power BI , Tableau , or another to craft analytics dashboards.

Data Warehouse 52

Data Warehouse Machine Learning Machine Learning Tableau 52

Pickl AI

AUGUST 11, 2024

These tables are called “factless fact tables” or “junction tables” They are used for modelling many-to-many relationships or for capturing timestamps of events. Dealing with Sparse Data In some cases, fact tables may contain a large number of null values due to missing data.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Best Practice 5.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

Pickl AI

FEBRUARY 21, 2023

Why is Data Mining Important? Data mining is often used to build predictive models that can be used to forecast future events. It can be helpful for businesses looking to forecast demand, identify potential customers, or anticipate changes in the market.

Data Mining 52

Data Mining Data Mining Data Mining Data Scientist 52

ODSC - Open Data Science

JANUARY 18, 2024

They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable. These professionals will work with their colleagues to ensure that data is accessible, with proper access. The reason this is an important skill is that ETL is a critical process for data warehousing and business intelligence.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

databricks

JUNE 12, 2025

Events Data + AI Summit Data + AI World Tour Data Intelligence Days Event Calendar Blog and Podcasts Databricks Blog Explore news, product announcements, and more Databricks Mosaic Research Blog Discover the latest in our Gen AI research Data Brew Podcast Let’s talk data!

SQL 245

SQL Data Engineering Data Engineer Data Engineering 245

Alation

FEBRUARY 13, 2020

This was an eventful year in the world of data and analytics. billion merger of Cloudera and Hortonworks, the widely scrutinized GDPR (General Data Protection Regulation), or the Cambridge Analytica scandal that rocked Facebook. Amid the headline grabbing news, 2018 will also be remembered as the year of the data catalog.

Data Governance 52

Data Governance Machine Learning Machine Learning Analytics 52

Data Science Blog

FEBRUARY 7, 2023

Das Format Business Talk am Kudamm in Berlin führte ein Interview mit Benjamin Aunkofer zum Thema “Business Intelligence und Process Mining nachhaltig umsetzen”. Für Data Science ja sowieso. Ein Data Warehouse ist eine oder eine Menge von Datenbanken. Und sie liegen damit natürlich vollkommen richtig.

Business Intelligence 286

Business Intelligence Business Intelligence Data Warehouse Data Lakes 286

phData

JULY 14, 2023

You can store and access your structured, semi-structured, and unstructured data in one location and gain seamless access to external data with similar scale and speed. Snowflake’s cloud-based data warehouse can be used to store and query large amounts of data from multiple sources, such as ad networks, DSPs, and SSPs.

Analytics 52

Analytics Analytics Machine Learning Machine Learning 52

Alation

APRIL 14, 2022

Supports the ability to interact with the actual data and perform analysis on it. This provides the facility a time or event for a job to run and offers useful post-run information. Similar to a data warehouse schema, this prep tool automates the development of the recipe to match. Scheduling. Target Matching.

Data Governance 59

Data Governance ML ML Cloud Data 59

phData

FEBRUARY 27, 2024

The Snowflake Data Cloud is a cloud-based data warehouse that is becoming increasingly popular among businesses of all sizes. Snowflake is highly scalable and easy to manage within one account for most businesses, but when is it beneficial to use multiple accounts in Snowflake?

Database 52

Database Data Governance Data Silos Data Warehouse 52

phData

NOVEMBER 13, 2023

Seamless Integration with Downstream Tools: The setup process is tailored to enable consistent metric access across a variety of analytics and business intelligence tools. These jobs can be triggered via schedule or events, ensuring your data assets are always up-to-date.

Database 52

Database Business Intelligence Business Intelligence Data Silos 52

Alation

AUGUST 26, 2021

For this reason, data intelligence software has increasingly leveraged artificial intelligence and machine learning (AI and ML) to automate curation activities, which deliver trustworthy data to those who need it. How Do Data Intelligence Tools Support Data Culture? BI and AI for Data Intelligence.

Data Governance 64

Data Governance ML ML Augmented Analytics 64

DagsHub

AUGUST 23, 2024

Data Quality Dimensions Data quality dimensions are the criteria that are used to evaluate and measure the quality of data. These include the following: Accuracy indicates how correctly data reflects the real-world entities or events it represents. It is SQL-based and integrates well with modern data warehouses.

Data Quality 52

Data Quality Data Governance Machine Learning Machine Learning 52

Data Science Blog

MARCH 30, 2023

Diese Anwendungsfälle sind jedoch analytisch recht trivial und bereits mit einfacher BI (Business Intelligence) oder dedizierten Analysen ganz ohne Process Mining bereits viel schneller aufzuspüren. Jedes Process Mining Tool benötigt pro Use Case mindestens ein Event Log. Idealerweise werden nur fertige Event-Logs bzw.

Data Warehouse 147

Data Warehouse Business Intelligence Business Intelligence Power BI 147