Pickl AI

NOVEMBER 15, 2023

Discover the nuanced dissimilarities between Data Lakes and Data Warehouses. Data management in the digital age has become a crucial aspect of businesses, and two prominent concepts in this realm are Data Lakes and Data Warehouses. It acts as a repository for storing all the data.

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ODSC - Open Data Science

JUNE 7, 2023

To make your data management processes easier, here’s a primer on data lakes, and our picks for a few data lake vendors worth considering. What is a data lake? First, a data lake is a centralized repository that allows users or an organization to store and analyze large volumes of data.

Data Lakes 52

Data Lakes Azure Data Warehouse Hadoop 52

AWS Machine Learning Blog

DECEMBER 3, 2024

Amazon Q Business is a generative AI-powered assistant that can answer questions, provide summaries, generate content, and securely complete tasks based on data and information in your enterprise systems. For more information, see Configure Amazon Q Business with AWS IAM Identity Center trusted identity propagation.

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AWS Database Data Silos Data Lakes 99

Dataversity

APRIL 23, 2021

Within the Data Management industry, it’s becoming clear that the old model of rounding up massive amounts of data, dumping it into a data lake, and building an API to extract needed information isn’t working. Click to learn more about author Brian Platz.

Database 90

Database Data Lakes Data Silos Data Governance 90

phData

NOVEMBER 9, 2023

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. What Components Make up the Snowflake Data Cloud? What is a Data Lake? What is the Difference Between a Data Lake and a Data Warehouse?

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98

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.* Analytics data catalog. Data integration. Loss of visibility after data leaves EDW.

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.* Analytics data catalog. Data integration. Loss of visibility after data leaves EDW.

Tableau 98

Tableau Data Quality Analytics Analytics 98

Alation

FEBRUARY 1, 2022

Ventana found that the most time-consuming part of an organization’s analytic efforts is accessing and preparing data; this is the case for more than one-half (55%) of respondents. 1 Data catalogs can significantly reduce this burden by making it easier for analysts to find and access relevant information.

Data Lakes 52

Data Lakes Data Governance ML ML 52

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. All phases of the data-information lifecycle.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Alation

MARCH 21, 2023

While this industry has used data and analytics for a long time, many large travel organizations still struggle with data silos , which prevent them from gaining the most value from their data. What is big data in the travel and tourism industry? What is big data in the travel and tourism industry?

Analytics 52

Analytics Analytics Data Silos Big Data 52

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

AWS Machine Learning Blog

JUNE 13, 2025

Whether it’s for generating more relevant responses, summarizing information, or handling nuanced queries, choosing the best model is key to providing optimal performance. Even the best FMs will not have access to the latest or domain-specific information critical to your business.

AI 86

AI AI AWS Database 86

Pickl AI

OCTOBER 6, 2024

Understanding these methods helps organizations optimize their data workflows for better decision-making. Introduction In today’s data-driven world, efficient data processing is crucial for informed decision-making and business growth. Load After extraction, the next step is Load. Conversely, ELT flips this sequence.

ETL 52

ETL Data Warehouse Data Quality Data Lakes 52

Alation

APRIL 19, 2022

And in an increasingly remote workforce, people need to access data systems easily to do their jobs. Today, data dwells everywhere. Data modernization enables informed decision making by pulling data out of systems more reliably. It helps you identify high-value data combinations and integrations.

Data Governance 52

Data Governance Cloud Data Database Data Silos 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. This enables your organization to extract valuable insights and drive informed decision-making.

Data Quality 45

Data Quality AI AI Database 45

IBM Journey to AI blog

FEBRUARY 2, 2023

Misconception 1: Cloud data warehouses are more expensive When considering moving data warehouses from on-premises to the cloud, companies often get sticker shock at the total cost of ownership. However, a more detailed analysis is needed to make an informed decision.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

Alation

JANUARY 27, 2022

As an organization embraces digital transformation , more data is available to inform decisions. To use that data, decision-makers across the company will need to have access. However, opening the floodgates of information comes with challenges. Inform Decision Making. What Are the Top Data Challenges to Analytics?

Data Governance 52

Data Governance Analytics Analytics Data Quality 52

Pickl AI

JUNE 28, 2023

What is Data Mining? In today’s data-driven world, organizations collect vast amounts of data from various sources. Information like customer interactions, and sales transactions plays a pivotal role in decision-making. But, this data is often stored in disparate systems and formats.

Data Mining 52

Data Mining Data Mining Data Mining ETL 52

Pickl AI

DECEMBER 11, 2024

Understanding Lean Data Management Lean data management revolves around four core principles: accuracy , relevance , accessibility , and efficiency. Accurate data ensures decisions are grounded in reliable information. Relevance prioritises the most critical data for organisational goals, eliminating unnecessary noise.

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Data Silos Data Pipeline Artificial Intelligence Artificial Intelligence 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.

Data Silos 52

Data Silos Database Data Quality Data Engineering 52

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

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.

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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.

Cloud Data 98

Cloud Data Data Silos Data Lakes Data Warehouse 98

Alation

AUGUST 2, 2022

Using data to understand customers’ needs allows you to: Provide meaningful educational marketing materials. Ensure that customers have the information they need. The problem many companies face is that each department has its own data, technologies, and information handling processes. Accelerate the sales cycle.

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Alation

JUNE 7, 2023

So, ARC worked to make data more accessible across domains while capturing tribal knowledge in the data catalog; this reduced the subject-matter-expertise bottlenecks during product development and accelerated higher quality analysis. In addition to an AWS S3 Data Lake and Snowflake Data Cloud, ARC also chose Alation Data Catalog.

Data Silos 52

Data Silos Data Lakes Data Governance Business Intelligence 52

Alation

APRIL 7, 2021

A data catalog contains critical metadata (like schema information), which need to be secure and available to consumers at all times. Hence, the data catalog must be protected by enterprise-grade security. The cloud unifies a distributed data landscape. Enjoy the peace of mind of always-on security.

Data Governance 52

Data Governance Data Silos Data Lakes AWS 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

Dataversity

FEBRUARY 17, 2022

With machine learning (ML) and artificial intelligence (AI) applications becoming more business-critical, organizations are in the race to advance their AI/ML capabilities. To realize the full potential of AI/ML, having the right underlying machine learning platform is a prerequisite.

Machine Learning 52

Machine Learning Machine Learning ML ML 52

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.

ETL 59

ETL Data Pipeline ML ML 59

AWS Machine Learning Blog

NOVEMBER 1, 2024

Decentralized clinical trials, however, often employ a singular data lake for all of an organization’s clinical trials. With a centralized data lake, organizations can avoid the duplication of data across separate trial databases.

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Flipboard

DECEMBER 4, 2024

The use of separate data warehouses and lakes has created data silos, leading to problems such as lack of interoperability, duplicate governance efforts, complex architectures, and slower time to value. You can use Amazon SageMaker Lakehouse to achieve unified access to data in both data warehouses and data lakes.

Data Lakes 139

Data Lakes Data Warehouse AWS Database 139

phData

SEPTEMBER 27, 2024

Transitional modeling is like the Lego of the customer data world. Instead of trying to build a perfect, complete customer model from the get-go, it starts with small, standardized pieces of information – let’s call them data atoms (or atomic data). Let’s look at an example. Who performed the action?

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52