Unite.AI

DECEMBER 5, 2023

ETL ( Extract, Transform, Load ) Pipeline: It is a data integration mechanism responsible for extracting data from data sources, transforming it into a suitable format, and loading it into the data destination like a data warehouse. The pipeline ensures correct, complete, and consistent data.

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Marktechpost

JUNE 5, 2024

As a result, it’s easier to find problems with data quality, inconsistencies, and outliers in the dataset. Metadata analysis is the first step in establishing the association, and subsequent steps involve refining the relationships between individual database variables. The 18 best data profiling tools are listed below.

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IBM Journey to AI blog

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

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Unite.AI

JUNE 13, 2024

How is data.world investing in research and development to stay at the forefront of AI and data integration technologies? We’re committed to staying at the bleeding edge of what’s possible in AI and data integration. Instead, we aim to eliminate the need for users to query their data altogether.

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IBM Journey to AI blog

JANUARY 17, 2023

IBM Cloud Pak for Data Express solutions offer clients a simple on ramp to start realizing the business value of a modern architecture. Data governance. The data governance capability of a data fabric focuses on the collection, management and automation of an organization’s data. Data integration.

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IBM Journey to AI blog

OCTOBER 12, 2023

Among the tasks necessary for internal and external compliance is the ability to report on the metadata of an AI model. Metadata includes details specific to an AI model such as: The AI model’s creation (when it was created, who created it, etc.)

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Marktechpost

MAY 9, 2024

Because of the platform’s versatility in handling different document kinds and layouts, data scientists may effectively preprocess data at scale without being constrained by issues with format or cleaning. The main features of the platform which are meant to make data workflows more efficient are as follows.

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IBM Journey to AI blog

JUNE 28, 2024

Building knowledge graphs : Generative AI can automatically build comprehensive knowledge graphs by understanding the intricate data models of different vendors. These knowledge graphs represent data entities and their relationships, providing a structured and interconnected view of the vendor ecosystem.

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Marktechpost

MAY 15, 2024

The training of generative models, such as GPT-4, Gemini, Cluade, and others, relies on often insufficiently documented and vetted data. This unstructured and obscure data collection poses severe challenges in maintaining data integrity and ethical standards.

Metadata 112

Metadata Artificial Intelligence Artificial Intelligence AI Development 112

IBM Journey to AI blog

JUNE 17, 2024

Some of the common challenges that enterprises face when protecting data are: Maintaining data integrity and privacy amid the threat of potential data breaches and data leaks. Managing IT budgets while dealing with increased cyberthreats and regulatory compliance.

Metadata 124

Metadata Data Integration AI AI 124

The MLOps Blog

JUNE 27, 2023

When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. When thinking about a tool for metadata storage and management, you should consider: General business-related items : Pricing model, security, and support. Can you compare images?

Metadata 134

Metadata Machine Learning Data Scientist Data Quality 134

IBM Journey to AI blog

JANUARY 5, 2023

Both approaches were typically monolithic and centralized architectures organized around mechanical functions of data ingestion, processing, cleansing, aggregation, and serving. Monitor and identify data quality issues closer to the source to mitigate the potential impact on downstream processes or workloads.

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Data Quality Metadata ETL Big Data 130

IBM Journey to AI blog

AUGUST 7, 2023

Transparency throughout the data lifecycle and the ability to demonstrate data integrity and consistency are critical factors for improvement. The ledger delivers tamper evidence, enabling the detection of any modifications made to the data, even if carried out by privileged users.

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Marktechpost

JULY 7, 2024

Item Tower: Encodes item features like metadata, content characteristics, and contextual information. While these systems enhance user engagement and drive revenue, they also present challenges like data quality and privacy concerns.

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Algorithm Neural Network Metadata Large Language Models 100

Pickl AI

JULY 19, 2024

They enhance data integrity, security, and accessibility while providing tools for efficient data management and retrieval. A Database Management System (DBMS) is specialised software designed to efficiently manage and organise data within a computer system. Indices are data structures optimised for rapid data retrieval.

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ODSC - Open Data Science

SEPTEMBER 27, 2023

They excel at managing structured data and supporting ACID (Atomicity, Consistency, Isolation, Durability) transactions. Scalability: Relational databases can scale vertically by upgrading hardware, but horizontal scaling can be more challenging due to the need to maintain data integrity and relationships.

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Big Data Metadata ETL Business Intelligence 98

Pickl AI

OCTOBER 11, 2024

These include the database engine for executing queries, the query processor for interpreting SQL commands, the storage manager for handling physical data storage, and the transaction manager for ensuring data integrity through ACID properties. Data Independence: Changes in database structure do not affect application programs.

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Data Integration Metadata Big Data Algorithm 52

AWS Machine Learning Blog

MAY 15, 2023

Among those algorithms, deep/neural networks are more suitable for e-commerce forecasting problems as they accept item metadata features, forward-looking features for campaign and marketing activities, and – most importantly – related time series features. She has 12 years of software development and architecture experience.

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Convolutional Neural Networks Neural Network Metadata Data Scientist 82

Pickl AI

OCTOBER 21, 2024

The primary purpose of a DBMS is to provide a systematic way to manage large amounts of data, ensuring that it is organised, accessible, and secure. By employing a DBMS, organisations can maintain data integrity, reduce redundancy, and streamline data operations, enabling more informed decision-making.

Metadata 52

Metadata Data Integration Machine Learning Algorithm 52

Unite.AI

SEPTEMBER 18, 2023

Authority Management Access control is a security & privacy technology that is used to restrict a user’s access to authorized resources on the basis of pre-defined rules, set of instructions, policies, safeguarding data integrity, and system security.

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Pickl AI

AUGUST 31, 2023

Types of Data Profiling: Data profiling can be broadly categorized into three main types, each focusing on different aspects of the data: Structural Profiling: Structural profiling involves analyzing the structure and metadata of the data. It supports metadata analysis, data lineage, and data quality assessment.

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ETL Data Quality Data Integration Metadata 52

Pickl AI

JULY 30, 2024

Its architecture includes FlowFiles, repositories, and processors, enabling efficient data processing and transformation. With a user-friendly interface and robust features, NiFi simplifies complex data workflows and enhances real-time data integration. How Does Apache NiFi Ensure Data Integrity?

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Data Ingestion ETL Big Data Data Integration 52

IBM Journey to AI blog

JULY 1, 2024

Irina Steenbeek introduces the concept of descriptive lineage as “a method to record metadata-based data lineage manually in a repository.” Extraction, transformation and loading (ETL) tools dominated the data integration scene at the time, used primarily for data warehousing and business intelligence.

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The MLOps Blog

MAY 10, 2023

Packaging models with PMML Using the PMML library in Python, you can export your machine learning models to PMML format and then deploy that as a web service, a batch processing system, or a data integration platform. Finally, you can store the model and other metadata information using the INSERT INTO command.

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Python Metadata ML Deep Learning 105

Pickl AI

OCTOBER 8, 2024

Access Transparency Users experience seamless access to files, as the system hides the complexities of how data distributed across various servers. This includes features like coherent access, where changes made to files are instantly visible across the network. This centralization aids in efficient file management and coordination.

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ODSC - Open Data Science

JUNE 7, 2023

Data lakes are able to handle a diverse range of data types. From images, videos, text, and even sensor data. Then, there’s data integration. A data lake can also act as a central hub for integrating data from various sources and systems within an organization.

Metadata 52

Metadata Data Science Machine Learning Python 52

IBM Journey to AI blog

SEPTEMBER 17, 2024

Its in-memory processing helps to ensure that data is ready for quick analysis and reporting, enabling real-time what-if scenarios and reports without lag. Our solution handles massive multidimensional cubes seamlessly, enabling you to maintain a complete view of your data without sacrificing performance or data integrity.

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Big Data Metadata Business Intelligence Data Integration 100

ODSC - Open Data Science

OCTOBER 18, 2024

This comprehensive guide covers practical frameworks to enable effective holistic scoping, planning, governance, and deployment of project management for data science. Proper management and strategic stakeholder alignment allow data science leaders to avoid common missteps and accelerate ROI.

Data Science 52

Data Science ETL Data Scientist Data Quality 52

Pickl AI

JUNE 28, 2023

With the use of these tools, one can streamline the data modelling process. Moreover, these tools are designed to automate tasks like generating SQL scripts, documenting metadata and others. Improved Visualization Data modelling tools offer intuitive graphical representations of data models.

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Metadata Data Integration Automation Software Development 52

AWS Machine Learning Blog

JUNE 21, 2024

eSentire has over 2 TB of signal data stored in their Amazon Simple Storage Service (Amazon S3) data lake. eSentire used gigabytes of additional human investigation metadata to perform supervised fine-tuning on Llama 2. They needed no additional infrastructure for data integration.

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AWS Machine Learning Blog

OCTOBER 2, 2024

However, scaling up generative AI and making adoption easier for different lines of businesses (LOBs) comes with challenges around making sure data privacy and security, legal, compliance, and operational complexities are governed on an organizational level. In this post, we discuss how to address these challenges holistically.

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AWS Machine Learning Blog

NOVEMBER 15, 2023

In this post, we demonstrate how data aggregated within the AWS CCI Post Call Analytics solution allowed Principal to gain visibility into their contact center interactions, better understand the customer journey, and improve the overall experience between contact channels while also maintaining data integrity and security.

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Pickl AI

OCTOBER 11, 2023

This process involves real-time monitoring and documentation to provide visibility on the data quality, thereby helping the organization detect and address data-related issues. It is backed by sophisticated algorithms that empower the identification of budding data irregularities Simplify the amalgamation of data from diverse origins.

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Data Quality Metadata Automation Data Science 52

Pickl AI

APRIL 14, 2023

Data Processes and Organizational Structure Data Governance access controls enable the end-users to see how data processing works inside an organization. It can include data refresh cadences, PII limitations, regulatory data regulations, or even data access. It ensures the safe storage of data.

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Pickl AI

NOVEMBER 15, 2023

From financial services to e-commerce and telecommunications, organizations leverage Data Warehouses to unlock the full potential of their structured data for strategic advantage. What Is Data Lake Architecture? Delta Lake vs. Data Lake Delta Lake is an open-source storage layer that brings ACID transactions to Data Lakes.

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ETL Metadata Business Intelligence Data Analysis 52

ODSC - Open Data Science

FEBRUARY 21, 2024

The use of the Terraform remote state , in particular, can be viewed from the perspective of data management , wherein accuracy, consistency, and efficiency are a must. These files contain metadata, current state details, and other information useful in planning and applying changes to infrastructure.

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AWS Machine Learning Blog

SEPTEMBER 28, 2023

Metadata about the request/response pairings are logged to Amazon CloudWatch. As an Information Technology Leader, Jay specializes in artificial intelligence, data integration, business intelligence, and user interface domains.

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