IBM Big Data Hub

SEPTEMBER 26, 2023

Pattern 4: Cloud data migration for analytics and insights. This strategy focuses on transferring existing data to the cloud and facilitating generation of advanced data analytics and insights, a key feature of modernized systems.

Cloud 88

Cloud Analytics Data migration Communications 88

IBM Big Data Hub

FEBRUARY 5, 2024

Migration cost Calculating cloud migration costs can be one of the most challenging aspects of migration. Solution: The best way to plan your cloud costs is by taking advantage of cloud migration planning tools that walk you through all the considerations of the cloud migration process.

Cloud 66

Cloud Data migration Digital transformation Risk 66

IBM Big Data Hub

SEPTEMBER 14, 2023

Broadly, the categories include the following: Application data exchange: Client/server communication between application components across clouds (e.g., via RESTful APIs) to exchange data and complete synchronous or asynchronous transactions.

Cloud 70

Cloud Financial Services Insurance Compliance 70

IBM Big Data Hub

JUNE 2, 2023

Migration to AWS with refactoring (auto-refactoring of code to Java/.Net). Data migration to the cloud for analytics and insights. Rearchitecting and modernizing with new channels of information delivery (leveraging microservices). For all these patterns, business functional equivalence is essential, as detailed below.

Cloud 79

Cloud Data migration Analytics IT 79

Collibra

JANUARY 18, 2023

Think about the challenges of controlling data quality, given that the creation mechanism is not exactly SDLC (Software Development Life Cycle). One could apply SDLC-like testing measures, for example, a lower environment stress test before data migration. So how should we work towards better Data Observability?

Data migration 52

Data migration Big data Analytics IT 52

IBM Big Data Hub

DECEMBER 7, 2023

However, organizations face challenges when adopting cloud-based OLAP solutions, such as: Data migration : Migrating large volumes of data to the cloud can be time-consuming and resource-intensive. Network latency : Geographic distances between data and users can introduce latency issues, affecting query performance.

Analytics 57

Analytics Cloud Artificial Intelligence Marketing 57

IBM Big Data Hub

JUNE 23, 2022

The data integration styles mentioned above are, of course, part of these improvements, but even more is available including automatic workload balancing and elastic scaling to help ensure you’re ready for high volumes of data.

Cloud 52

Cloud Metadata Government Data migration 52

Collibra

FEBRUARY 11, 2022

Multiple systems leading to a larger, more complex and more expensive hidden data factory. require data auditing and reporting. Data migrations – When moving large volumes of data to the cloud or to new storage, it’s important to identify missing records, values, and broken relationships across tables or systems.

IT 52

IT Analytics Metadata Sales 52

Reltio

JULY 23, 2019

In the past organisations often mobilized for large MDM programmes and had to retrospectively drive the governance throughout – now we are seeing that data governance is often leading – it has become a non-negotiable.”. If you’ve got people who already have an understanding of data and relevant skills, then you’ll accelerate your success.

MDM 40

MDM Cloud Analytics Marketing 40

ARMA International

SEPTEMBER 27, 2021

Moving to a cloud computing model may involve migrating data to the cloud; what and when to migrate will depend on factors that, in turn, will depend on the scope of the DT initiative and the CSF. The Proof of Concept (PoC) can help inform the approach to develop the data migration strategy. Business Continuity.

Digital transformation 59

Digital transformation Risk IT Computer and Electronics 59