ODSC - Open Data Science

JUNE 7, 2023

Data has to be stored somewhere. Data warehouses are repositories for your cleaned, processed data, but what about all that unstructured data your organization is starting to notice? What is a data lake? This can be structured, semi-structured, and even unstructured data. Where does it go?

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Data Lakes Azure Data Warehouse Hadoop 52

IBM Journey to AI blog

JUNE 15, 2023

There’s no debate that the volume and variety of data is exploding and that the associated costs are rising rapidly. The proliferation of data silos also inhibits the unification and enrichment of data which is essential to unlocking the new insights. Therefore, customers are looking for ways to reduce costs.

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Data Warehouse Data Lakes Analytics Analytics 110

Smart Data Collective

MARCH 21, 2022

More case studies are added every day and give a clear hint – data analytics are all set to change, again! . Data Management before the ‘Mesh’. In the early days, organizations used a central data warehouse to drive their data analytics. The cloud age did address that issue to a certain extent.

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Data Lakes Hadoop Data Silos Data Warehouse 75

IBM Journey to AI blog

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. Data lakehouse was created to solve these problems.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Pickl AI

OCTOBER 6, 2024

It is a crucial data integration process that involves moving data from multiple sources into a destination system, typically a data warehouse. This process enables organisations to consolidate their data for analysis and reporting, facilitating better decision-making. ETL stands for Extract, Transform, and Load.

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ETL Data Warehouse Data Quality Data Lakes 52

Tableau

APRIL 18, 2022

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Ensure the behaves the way you want it to— especially sensitive data and access. Data integration.

Tableau 102

Tableau Data Quality Analytics Analytics 102

Tableau

APRIL 18, 2022

What if the problem isn’t in the volume of data, but rather where it is located—and how hard it is to gather? Nine out of 10 IT leaders report that these disconnects, or data silos, create significant business challenges.* Ensure the behaves the way you want it to— especially sensitive data and access. Data integration.

Tableau 98

Tableau Data Quality Analytics Analytics 98

Precisely

JULY 18, 2024

Without access to all critical and relevant data, the data that emerges from a data fabric will have gaps that delay business insights required to innovate, mitigate risk, or improve operational efficiencies. You must be able to continuously catalog, profile, and identify the most frequently used data.

Data Lakes 52

Data Lakes Data Warehouse Data Governance Machine Learning 52

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.

Data Quality 52

Data Quality Data Lakes Data Warehouse Big Data 52

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.

AI 45

AI Data Quality AI Database 45

Pickl AI

JUNE 28, 2023

Understanding Data Integration in Data Mining Data integration is the process of combining data from different sources. Thus creating a consolidated view of the data while eliminating data silos. It ensures that the integrated data is available for analysis and reporting.

Data Mining 52

Data Mining Data Mining Data Mining ETL 52

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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AWS Database ETL AI 93

The MLOps Blog

MAY 17, 2023

These pipelines assist data scientists in saving time and effort by ensuring that the data is clean, properly formatted, and ready for use in machine learning tasks. Moreover, ETL pipelines play a crucial role in breaking down data silos and establishing a single source of truth.

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ETL Data Pipeline ML ML 59

phData

MAY 13, 2024

Even if organizations survive a migration to S/4 and HANA cloud, licensing and performance constraints make it difficult to perform advanced analytics on this data within the SAP environment.

Database 52

Database Analytics Analytics Machine Learning 52

Alation

APRIL 19, 2022

Data modernization is the process of transferring data to modern cloud-based databases from outdated or siloed legacy databases, including structured and unstructured data. In that sense, data modernization is synonymous with cloud migration. So what’s the appeal of this new infrastructure?

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

phData

SEPTEMBER 20, 2023

A data mesh is a decentralized approach to data architecture that’s been gaining traction as a solution to the challenges posed by large and complex data ecosystems. It’s all about breaking down data silos, empowering domain teams to take ownership of their data, and fostering a culture of data collaboration.

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Data Silos Database Data Quality Data Engineering 52

Dataversity

AUGUST 5, 2021

According to Gartner, data fabric is an architecture and set of data services that provides consistent functionality across a variety of environments, from on-premises to the cloud. Data fabric simplifies and integrates on-premises and cloud Data Management by accelerating digital transformation.

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Cloud Data Data Silos Data Lakes Data Warehouse 98

Dataversity

APRIL 5, 2021

However, most enterprises are hampered by data strategies that leave teams flat-footed when […]. The post Why the Next Generation of Data Management Begins with Data Fabrics appeared first on DATAVERSITY. Click to learn more about author Kendall Clark. The mandate for IT to deliver business value has never been stronger.

Internet of Things 97

Internet of Things Data Silos Data Lakes Data Warehouse 97

Alation

JANUARY 27, 2022

What Are the Top Data Challenges to Analytics? The proliferation of data sources means there is an increase in data volume that must be analyzed. Large volumes of data have led to the development of data lakes , data warehouses, and data management systems.

Data Governance 52

Data Governance Analytics Analytics Data Quality 52

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 […].

Analytics 69

Analytics Analytics Data Silos Data Lakes 69

Flipboard

DECEMBER 4, 2024

Currently, organizations often create custom solutions to connect these systems, but they want a more unified approach that them to choose the best tools while providing a streamlined experience for their data teams. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

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Data Lakes Data Warehouse AWS Database 139

AWS Machine Learning Blog

NOVEMBER 1, 2024

Instead, a core component of decentralized clinical trials is a secure, scalable data infrastructure with strong data analytics capabilities. Amazon Redshift is a fully managed cloud data warehouse that trial scientists can use to perform analytics.

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AWS Data Lakes Machine Learning Machine Learning 113

phData

SEPTEMBER 27, 2024

Both persistent staging and data lakes involve storing large amounts of raw data. But persistent staging is typically more structured and integrated into your overall customer data pipeline. You might choose a cloud data warehouse like the Snowflake AI Data Cloud or BigQuery. New user sign-up?

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52