Pickl AI

NOVEMBER 15, 2023

What Is Data Lake? A Data Lake is a centralized repository that allows businesses to store vast volumes of structured and unstructured data at any scale. Unlike traditional databases, Data Lakes enable storage without the need for a predefined schema, making them highly flexible.

Data Lakes 52

Data Lakes Data Warehouse Database ETL 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

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. They provide the backbone for a range of use cases such as business intelligence (BI) reporting, dashboarding, and machine-learning (ML)-based predictive analytics, that enable faster decision making and insights.

Data Warehouse 58

Data Warehouse Cloud Data Analytics Analytics 58

phData

FEBRUARY 27, 2024

Configuration for External Dependencies Third-party tools used with Snowflake, such as those for Single Sign On (SSO), Extract Load and Transform (ELT), and Business Intelligence (BI), all require configurations to the Snowflake account(s) where data resides. Establish data governance guidelines.

Database 52

Database Data Governance Data Silos Data Warehouse 52

IBM Journey to AI blog

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lakes 52

Data Lakes Data Warehouse Azure Apache Hadoop 52

Alation

JUNE 28, 2022

With a metadata management framework, your data analysts: Optimize search and findability: Create a single portal using role-based access for rapid data access based on job function and need. Establish business glossaries: Define business terms and create standard relationships for data governance.

Data Governance 52

Data Governance Data Analyst Machine Learning Machine Learning 52

ODSC - Open Data Science

SEPTEMBER 29, 2023

In today’s digital world, data is king. Organizations that can capture, store, format, and analyze data and apply the business intelligence gained through that analysis to their products or services can enjoy significant competitive advantages. But, the amount of data companies must manage is growing at a staggering rate.

Data Lakes 52

Data Lakes Clustering Big Data Big Data 52

Pickl AI

DECEMBER 4, 2023

Marketing Targeted Campaigns Increases campaign effectiveness and ROI Data silos leading to inconsistent information. Implementing integrated data management systems. Business Intelligence Analyst Focuses on transforming raw data into actionable business insights to support strategic decision-making.

Data Analysis 52

Data Analysis Data Analysis Artificial Intelligence Artificial Intelligence 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

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.

Data Lakes 139

Data Lakes Data Warehouse AWS Database 139

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?

Data Warehouse 98

Data Warehouse Data Lakes Clustering Cloud Data 98

phData

NOVEMBER 13, 2023

Enhanced Collaboration: dbt Mesh fosters a collaborative environment by using cross-project references, making it easy for teams to share, reference, and build upon each other’s work, eliminating the risk of data silos. Deploy jobs are designed to build into production databases, running sequentially to prevent conflicts.

Database 52

Database Business Intelligence Business Intelligence Data Silos 52

phData

FEBRUARY 13, 2024

Employing a modular structure, SAP ERP encompasses modules such as finance, human resources, supply chain , and more, facilitating real-time collaboration and data sharing across different departments through a centralized database. Violations of license restrictions can result in penalties, additional fees, or even legal consequences.

Analytics 59

Analytics Analytics Data Scientist Data Models 59

Alation

JULY 12, 2022

For instance, I have experienced machine learning libraries that worked on-premises but not for the cloud version of a database system. In some cases, you might need to keep some data or components on-premises. If it is a static legacy database, this can be a one-time deal. Utilize A Data Catalog To Classify and Label Data.

Cloud Data 52

Cloud Data Data Warehouse Database Machine Learning 52

AWS Machine Learning Blog

DECEMBER 3, 2024

Although generative AI is fueling transformative innovations, enterprises may still experience sharply divided data silos when it comes to enterprise knowledge, in particular between unstructured content (such as PDFs, Word documents, and HTML pages), and structured data (real-time data and reports stored in databases or data lakes).

AWS 84

AWS Database Data Silos Data Lakes 84

Precisely

FEBRUARY 17, 2025

Much of my career has been spent building data to accurately locate addresses for business intelligence (at GDT and Pitney Bowes) or navigation (at Tele Atlas and TomTom). Logistical Challenges: Data Accuracy: As mentioned above, address databases can be inaccurate or incomplete.

Data Silos 59

Data Silos Business Intelligence Business Intelligence Database 59

Dataconomy

MARCH 18, 2025

Data ingestion Data ingestion involves collecting various forms of datastructured, unstructured, and semi-structuredfrom multiple sources. This can include data at rest, such as databases, and data in motion, like live streaming data from IoT devices.

Machine Learning 91

Machine Learning Machine Learning Data Analysis Data Analysis 91