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

Alation

DECEMBER 14, 2021

It’s only been 15 years since AWS took the first steps to the cloud with S3 and EC2, which launched in 2006. With the database services launched soon after, developers had all the tools they needed to create applications without having to create the infrastructure to run them. What about other data sources? In Conclusion.

AWS 52

AWS Data Lakes Data Warehouse Machine Learning 52

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

ODSC - Open Data Science

NOVEMBER 19, 2024

Dimensional Data Modeling in the Modern Era by Dustin Dorsey Slides Dustin Dorsey’s AI slides explored the evolution of dimensional data modeling, a staple in data warehousing and business intelligence. Despite the rise of big data technologies and cloud computing, the principles of dimensional modeling remain relevant.

Deep Learning 52

Deep Learning Deep Learning Data Science AI 52

The MLOps Blog

JUNE 27, 2023

It integrates with Git and provides a Git-like interface for data versioning, allowing you to track changes, manage branches, and collaborate with data teams effectively. Dolt Dolt is an open-source relational database system built on Git. Severless GPUs are machines that scale-to-zero in the absence of traffic.

Machine Learning 134

Machine Learning Machine Learning ML ML 134

Precisely

JANUARY 19, 2023

Yet mainframes weren’t designed to integrate easily with modern distributed computing platforms. Cloud computing, object-oriented programming, open source software, and microservices came about long after mainframes had established themselves as a mature and highly dependable platform for business applications.

AWS 52

AWS Cloud Computing Data Pipeline Big Data 52

Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

SEPTEMBER 17, 2024

Streaming analytics tools enable organisations to analyse data as it flows in rather than waiting for batch processing. Variety Variety refers to the different types of data being generated. Technologies like stream processing enable organisations to analyse incoming data instantaneously.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

ODSC - Open Data Science

NOVEMBER 18, 2024

This session provides a gentle introduction to vector databases. You’ll start by demystifying what vector databases are, with clear definitions, simple explanations, and real-world examples of popular vector databases.

Deep Learning 40

Deep Learning Deep Learning Database Data Science 40

Pickl AI

APRIL 6, 2023

In-depth knowledge of distributed systems like Hadoop and Spart, along with computing platforms like Azure and AWS. Sound knowledge of relational databases or NoSQL databases like Cassandra. An example of the Azure Data Engineer Jobs in India can be evaluated as follows: 6-8 years of experience in the IT sector.

Azure 52

Azure Data Engineering Data Engineering Data Engineer 52

Pickl AI

OCTOBER 6, 2024

By employing ETL, businesses ensure that their data is reliable, accurate, and ready for analysis. This process is essential in environments where data originates from various systems, such as databases , applications, and web services. The key is to ensure that all relevant data is captured for further processing.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

ODSC - Open Data Science

JULY 11, 2023

Hybrid data centers: This refers to a combination of different data center solutions such as using a mix of on-premises, co-location, and cloud-based data centers to meet specific needs. Alternatives to using a data center: 1. They are typically used by organizations to store and manage their own data.

Data Lakes 40

Data Lakes AI AI Cloud Computing 40

IBM Journey to AI blog

JUNE 11, 2024

This involves rehosting applications on Amazon Elastic Compute Cloud (Amazon EC2 ) (link resides outside ibm.com) instances, which may require some reconfiguration of the applications to optimize them for the cloud environment.

AWS 85

AWS AI AI Data Lakes 85

Mlearning.ai

FEBRUARY 16, 2023

Thus, the solution allows for scaling data workloads independently from one another and seamlessly handling data warehousing, data lakes , data sharing, and engineering. Snowflake Database Pros Extensive Storage Opportunities Snowflake provides affordability, scalability, and a user-friendly interface.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

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

Alation

APRIL 14, 2022

Cloud providers like Amazon Web Services, Microsoft Azure, Google, and Alibaba not only provide capacity beyond what the data center can provide, their current and emerging capabilities and services drive the execution of AI/ML away from the data center. The future lies in the cloud. Cloud governance.

Data Governance 59

Data Governance ML ML Cloud Data 59

IBM Journey to AI blog

JULY 7, 2023

Learn how to create a holistic data protection strategy Staying on top of data security to keep ahead of ever-evolving threats Data security is the practice of protecting digital information from unauthorized access, corruption or theft throughout its entire lifecycle. Dispose of old computers and records securely.

Data Governance 40

Data Governance Data Lakes Database Cloud Computing 40

Pickl AI

SEPTEMBER 5, 2024

Microsoft Azure, often referred to as Azure, is a robust cloud computing platform developed by Microsoft. It offers a wide range of cloud services, including: Compute Power: Scalable virtual machines and container services for running applications.

Azure 52

Azure Data Scientist Data Science Machine Learning 52

AWS Machine Learning Blog

JANUARY 26, 2024

This is backed by our deep set of over 300 cloud security tools and the trust of our millions of customers, including the most security-sensitive organizations like government, healthcare, and financial services. With Security Lake, you can get a more complete understanding of your security data across your entire organization.

AWS 138

AWS ML ML AI 138