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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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.

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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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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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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?

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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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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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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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Pickl AI

AUGUST 31, 2023

However, analysis of data may involve partiality or incorrect insights in case the data quality is not adequate. Accordingly, the need for Data Profiling in ETL becomes important for ensuring higher data quality as per business requirements. What is Data Profiling in ETL?

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Pickl AI

OCTOBER 8, 2024

This blog will delve into the workings of DFS, its properties, applications, and best practices for implementation. Depth First Search (DFS) is a fundamental algorithm use in Artificial Intelligence and computer science for traversing or searching tree and graph data structures. What is Depth First Search?

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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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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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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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Pickl AI

JUNE 28, 2023

Thus helping the organisation comprehend the information hidden behind this data and make necessary decisions. Data modeling tools play a significant role in this. In this blog, we are going to explore some of the best data modelling tools and techniques, along with their key features.

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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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Pickl AI

APRIL 14, 2023

Falling into the wrong hands can lead to the illicit use of this data. Hence, adopting a Data Platform that assures complete data security and governance for an organization becomes paramount. In this blog, we are going to discuss more on What are Data platforms & Data Governance. Wrapping it up !!!

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Pickl AI

OCTOBER 11, 2023

Data Observability and Data Quality are two key aspects of data management. The focus of this blog is going to be on Data Observability tools and their key framework. The growing landscape of technology has motivated organizations to adopt newer ways to harness the power of data.

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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

NOVEMBER 15, 2023

Transactional databases, containing operational data generated by day-to-day business activities, feed into the Data Warehouse for analytical processing. From financial services to e-commerce and telecommunications, organizations leverage Data Warehouses to unlock the full potential of their structured data for strategic advantage.

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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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Pickl AI

MAY 15, 2023

Online Processing: this type of data processing involves managing transactional data in real time and focuses on handling individual transaction. The systems are designed to ensure data integrity, concurrency and quick response times for enabling interactive user transactions. The Data Science courses provided by Pickl.AI

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Pickl AI

OCTOBER 19, 2023

Whether you are a business executive making critical choices, a scientist conducting groundbreaking research, or simply an individual seeking accurate information, data quality is a paramount concern. The Relevance of Data Quality Data quality refers to the accuracy, completeness, consistency, and reliability of data.

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Pickl AI

OCTOBER 10, 2023

In this blog, we are going to unfold the two key aspects of data management that is Data Observability and Data Quality. Data is the lifeblood of the digital age. Today, every organization tries to explore the significant aspects of data and its applications. Expand Your Professional Growth with Pickl.AI

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Pickl AI

JULY 23, 2023

The ability to analyze and derive insights from vast amounts of data empowers businesses to make informed choices, optimize processes, and drive growth. In this blog, we will delve into four key types of analytics – Descriptive Analytics, Diagnostic Analytics, Predictive Analytics, and Prescriptive Analytics.

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The MLOps Blog

OCTOBER 3, 2023

There’s no component that stores metadata about this feature store? Mikiko Bazeley: In the case of the literal feature store, all it does is store features and metadata. We’re assuming that data scientists, for the most part, don’t want to write transformations elsewhere. Mikiko Bazeley: 100%.

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Artificial Corner

JUNE 6, 2023

The benefits of Databricks over Spark is Highly reliable and performant data pipelines and Productive data science at scale — source: [link] Databricks also introduced Delta Lake, an open-source storage layer that brings reliability to data lakes. MapReduce: simplified data processing on large clusters. Morgan Kaufmann.

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AWS Machine Learning Blog

AUGUST 7, 2024

The Amazon S3 PUT action invokes an AWS Lambda This Lambda function copies all the artifacts from the S3 bucket in the development account to another S3 bucket in the AI/ML governance account, providing restricted access and data integrity. This post assumes your accounts and S3 buckets are in the same AWS Region.

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Pickl AI

JUNE 11, 2024

But raw data alone isn’t enough to gain valuable insights. This is where data warehouses come in – powerful tools designed to transform raw data into actionable intelligence. This blog delves into the world of data warehouses, exploring their functionality, key features, and the latest innovations.

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IBM Journey to AI blog

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. It uses knowledge graphs, semantics and AI/ML technology to discover patterns in various types of metadata.

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