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

APRIL 18, 2023

Data, technology, and improved trade execution could all be utilized by businesses to increase investment returns, spur innovation, and provide better investor experiences. The data-sharing features of Snowflake enable enterprises to integrate their data without creating any data silos or building new technology capabilities.

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Pickl AI

JUNE 28, 2023

But, this data is often stored in disparate systems and formats. Here comes the role of Data Mining. Read this blog to know more about Data Integration in Data Mining, The process encompasses various techniques that help filter useful data from the resource. Thereby, improving data quality and consistency.

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phData

NOVEMBER 9, 2023

This blog was originally written by Keith Smith and updated for 2024 by Justin Delisi. Snowflake’s Data Cloud has emerged as a leader in cloud data warehousing. The primary objective of this idea is to democratize data and make it transparent by breaking down data silos that cause friction when solving business problems.

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IBM Journey to AI blog

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases. Learn more about the benefits of data fabric and IBM Cloud Pak for Data.

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Pickl AI

NOVEMBER 15, 2023

This centralization streamlines data access, facilitating more efficient analysis and reducing the challenges associated with siloed information. With all data in one place, businesses can break down data silos and gain holistic insights. What Is a Data Warehouse? What is meant by Data Lake?

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IBM Journey to AI blog

JULY 3, 2024

Open is creating a foundation for storing, managing, integrating and accessing data built on open and interoperable capabilities that span hybrid cloud deployments, data storage, data formats, query engines, governance and metadata. With an open data lakehouse, you can access a single copy of data wherever your data resides.

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IBM Journey to AI blog

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

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Dataversity

APRIL 1, 2021

In the data-driven world we live in today, the field of analytics has become increasingly important to remain competitive in business. In fact, a study by McKinsey Global Institute shows that data-driven organizations are 23 times more likely to outperform competitors in customer acquisition and nine times […].

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Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. SageMaker Unified Studio provides a unified experience for using data, analytics, and AI capabilities.

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