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. Defining OLAP today OLAP database systems have significantly evolved since their inception in the early 1990s.

Data Preparation 72

Data Preparation Database Data Analysis Data Analysis 72

IBM Journey to AI blog

OCTOBER 30, 2023

Overall, this partnership enables the retailer to make data-driven decisions, improve supply chain efficiency and ultimately boost customer satisfaction, all in a secure and scalable cloud environment. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

AWS 95

AWS AI AI Data Warehouse 95

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

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

AWS Machine Learning Blog

MAY 8, 2024

SageMaker Feature Store – By using a centralized repository for ML features, SageMaker Feature Store enhances data consumption and facilitates experimentation with validation data. Instead of directly ingesting data from the data warehouse, the required features for training and inference steps are taken from the feature store.

ML 124

ML ML AWS AI 124

IBM Journey to AI blog

JULY 17, 2023

Through workload optimization across multiple query engines and storage tiers, organizations can reduce data warehouse costs by up to 50 percent. 1 Watsonx.data offers built-in governance and automation to get to trusted insights within minutes, and integrations with existing databases and tools to simplify setup and user experience.

AI 74

AI AI Machine Learning Machine Learning 74

Pickl AI

JULY 23, 2023

Using the right data analytics techniques can help in extracting meaningful insight, and using the same to formulate strategies. The analytics techniques like descriptive analytics, predictive analytics, diagnostic analytics and others find application in diverse industries, including retail, healthcare, finance, and marketing.

Analytics 52

Analytics Analytics Predictive Analytics Data Analysis 52

phData

DECEMBER 12, 2023

Snowflake’s built-for-the-cloud architecture is highly performant and designed to handle large volumes of data and data consumers. Because of its cloud architecture, users do not have to worry about the maintenance of the infrastructure and the database going down at an inopportune time.

Data Warehouse 52

Data Warehouse Machine Learning Machine Learning Tableau 52

Pickl AI

JANUARY 28, 2025

They encompass all the origins from which data is collected, including: Internal Data Sources: These include databases, enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, and flat files within an organization. Data can be structured (e.g., databases), semi-structured (e.g.,

Business Intelligence 52

Business Intelligence Business Intelligence ETL Data Lakes 52

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

Pickl AI

JANUARY 15, 2025

These tools enable organizations to convert raw data into actionable insights through various means such as reporting, analytics, data visualization, and performance management. Data Processing: Cleaning and organizing data for analysis. How Do I Choose the Right BI Tool for My Organization?

Business Intelligence 52

Business Intelligence Business Intelligence Power BI Data Visualization 52

Pickl AI

JULY 3, 2023

Here are steps you can follow to pursue a career as a BI Developer: Acquire a solid foundation in data and analytics: Start by building a strong understanding of data concepts, relational databases, SQL (Structured Query Language), and data modeling.

Business Intelligence 52

Business Intelligence Business Intelligence SQL Data Visualization 52

phData

APRIL 18, 2023

Snowflake’s data sharing enables AMCs to join internal data with third-party market data, as well as data that sits across applications and data warehouses. Closing As the financial industry increasingly becomes more data-driven, the demand for futuristic, cloud-based solutions will continue to grow.

Data Silos 52

Data Silos ETL Clustering Analytics 52

Pickl AI

SEPTEMBER 18, 2024

It utilises Amazon Web Services (AWS) as its main data lake, processing over 550 billion events daily—equivalent to approximately 1.3 petabytes of data. The architecture is divided into two main categories: data at rest and data in motion. What Technologies Does Netflix Use for Its Big Data Infrastructure?

Big Data 52

Big Data Big Data Apache Kafka Big Data Analytics 52

Pickl AI

JULY 29, 2024

Log Analysis These are well-suited for analysing log data from various sources, such as web servers, application logs, and sensor data, to gain insights into user behaviour and system performance. Integration with Existing Systems Integrating a Hadoop cluster with existing data processing systems and applications can be complex.

Hadoop 52

Hadoop Clustering Big Data Big Data 52

phData

SEPTEMBER 27, 2024

. “ This sounds great in theory, but how does it work in practice with customer data or something like a ‘composable CDP’? Well, implementing transitional modeling does require a shift in how we think about and work with customer data. It often involves specialized databases designed to handle this kind of atomic, temporal data.

Data Modeling 52

Data Modeling Data Models Apache Kafka Data Lakes 52

ODSC - Open Data Science

NOVEMBER 22, 2023

Data Version Control for Data Lakes: Handling the Changes in Large Scale 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.

Data Lakes 52

Data Lakes Predictive Analytics AI AI 52