ODSC - Open Data Science

FEBRUARY 24, 2023

Metabase GitHub | Website Metabase is an easy-to-use data exploration tool that allows even non-technical users to ask questions and gain insights. This business intelligence and user experience tool allows you to build interactive dashboards, models for cleaning tables, and set up alerts to notify users when your data changes.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. Business intelligence (BI) platforms. Better Data Culture.

Data Warehouse 52

Data Warehouse ETL Tableau Cloud Data 52

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

IBM Journey to AI blog

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. Trustworthiness is critical.

AI 88

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Dataconomy

SEPTEMBER 27, 2023

Data science and analytics MCSA and MCSE certifications can also lead to roles in data science and analytics, such as data analyst, data scientist, or business intelligence developer. Data analysts collect, clean, and analyze data to extract insights that can help businesses make better decisions.

Database Administration 113

Database Administration Database Azure Cloud Computing 113

Alation

OCTOBER 21, 2021

But, on the back end, data lakes give businesses a common repository to collect and store data, streamlined usage from a single source, and access to the raw data necessary for today’s advanced analytics and artificial intelligence (AI) needs. Alation & Your Data.

Data Lakes 52

Data Lakes Data Governance Data Warehouse Business Intelligence 52

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. You only pay for the resources you use.

Database 97

Database Data Science Big Data Big Data 97

IBM Journey to AI blog

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 94

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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. Today, OLAP database systems have become comprehensive and integrated data analytics platforms, addressing the diverse needs of modern businesses.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

IBM Journey to AI blog

JULY 11, 2023

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 60

Data Warehouse Database Cloud Data Big Data 60

IBM Journey to AI blog

AUGUST 28, 2023

It’s no wonder then that Macmillan needs sophisticated business intelligence (BI) and data analytics. This approach would center on a “self-service” model, empowering users to source and share key data. To further add value, the team brought Cognos Analytics end-user training in-house.

Analytics 64

Analytics Analytics Business Intelligence Business Intelligence 64

IBM Journey to AI blog

JULY 3, 2024

This includes integration with your data warehouse engines, which now must balance real-time data processing and decision-making with cost-effective object storage, open source technologies and a shared metadata layer to share data seamlessly with your data lakehouse.

AI 45

AI AI Data Quality Database 45

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

JULY 17, 2023

It is supported by querying, governance, and open data formats to access and share data across the hybrid cloud. Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent.

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IBM Journey to AI blog

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

AI 93

AI AI Data Scientist Data Governance 93

ODSC - Open Data Science

FEBRUARY 6, 2024

This open-source streaming platform enables the handling of high-throughput data feeds, ensuring that data pipelines are efficient, reliable, and capable of handling massive volumes of data in real-time. Each platform offers unique features and benefits, making it vital for data engineers to understand their differences.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

DataSeries

JANUARY 18, 2023

Classical data systems are founded on this story. Nonetheless, the truth is slowing starting to emerge… The value of data is not in insights Most dashboards fail to provide useful insights and quickly become derelict. We increasingly refer to these technologies collectively as Artificial Intelligence (AI).

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Data Warehouse Deep Learning 52

AWS Machine Learning Blog

OCTOBER 9, 2024

Using Amazon Redshift ML for anomaly detection Amazon Redshift ML makes it easy to create, train, and apply machine learning models using familiar SQL commands in Amazon Redshift data warehouses. There are no additional costs to using Redshift ML for anomaly detection. To learn more, see the documentation.

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AWS ML ML Data Quality 87

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.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

AWS Machine Learning Blog

JUNE 25, 2024

Amazon Bedrock , a fully managed service designed to facilitate the integration of LLMs into enterprise applications, offers a choice of high-performing LLMs from leading artificial intelligence (AI) companies like Anthropic, Mistral AI, Meta, and Amazon through a single API. The LLM generates output based on the user prompt.

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IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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phData

SEPTEMBER 25, 2024

In this blog, we will provide a comprehensive overview of ETL considerations, introduce key tools such as Fivetran, Salesforce, and Snowflake AI Data Cloud , and demonstrate how to set up a pipeline and ingest data between Salesforce and Snowflake using Fivetran. It can onboard chunks of data from different systems into one.

ETL 52

ETL Database Data Warehouse Analytics 52

Pickl AI

DECEMBER 10, 2024

Exalytics: The In-Memory Analytics Machine Oracle Exalytics is a pioneering solution for in-memory analytics and business intelligence. By leveraging cutting-edge hardware and software integration, Exalytics enables businesses to analyse large datasets in real-time.

Database 52

Database Analytics Analytics Business Intelligence 52

Pickl AI

APRIL 26, 2024

The mode is the value that appears most frequently in a data set. Machine learning is a subset of artificial intelligence that enables computers to learn from data and improve over time without being explicitly programmed. Data Warehousing and ETL Processes What is a data warehouse, and why is it important?

Data Analyst 52

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ODSC - Open Data Science

JANUARY 18, 2024

ETL (Extract, Transform, Load) This is a core data engineering process for moving data from one or more sources to a destination, typically a data warehouse or data lake. 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

DagsHub

NOVEMBER 11, 2024

Social media conversations, comments, customer reviews, and image data are unstructured in nature and hold valuable insights, many of which are still being uncovered through advanced techniques like Natural Language Processing (NLP) and machine learning. Many find themselves swamped by the volume and complexity of unstructured data.

AI 52

AI AI Data Lakes Database 52

AWS Machine Learning Blog

APRIL 3, 2025

OMRONs data strategyrepresented on ODAPalso allowed the organization to unlock generative AI use cases focused on tangible business outcomes and enhanced productivity. One key initiative is ODAPChat, an AI-powered chat-based assistant employees can use to interact with data using natural language queries.

AWS 74

AWS Data Governance Data Silos SQL 74

phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 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?

Data Governance 64

Data Governance ML ML Augmented Analytics 64

IBM Journey to AI blog

AUGUST 4, 2023

It’s distributed both in the cloud and on-premises, allowing extensive use and movement across clouds, apps and networks, as well as stores of data at rest. An architecture designed for data democratization aims to be flexible, integrated, agile and secure to enable the use of data and artificial intelligence (AI) at scale.

Data Lakes 73

Data Lakes AI AI Data Governance 73

Dataconomy

NOVEMBER 19, 2024

So, if we compare data to oil, it suggests everyone has access to the same data, though in different quantities and easier to harvest for some. This comparison makes data feel like a commodity, available to everyone but processed in different ways. It all actually started with business intelligence.

AI 113

AI AI Business Intelligence Business Intelligence 113