IBM Journey to AI blog

DECEMBER 16, 2022

So, instead of wandering the aisles in hopes you’ll stumble across the book, you can walk straight to it and get the information you want much faster. 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.

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IBM Journey to AI blog

OCTOBER 17, 2024

AI-powered features in Cognos Analytics today IBM has embedded AI throughout Cognos Analytics to streamline processes, enhance data discovery and enable users to gain deeper insights with minimal effort. These insights help users fully understand their data.

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IBM Journey to AI blog

MAY 9, 2023

Supporting the data management life cycle According to IDC’s Global StorageSphere, enterprise data stored in data centers will grow at a compound annual growth rate of 30% between 2021-2026. [2] ” Notably, watsonx.data runs both on-premises and across multicloud environments.

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Flipboard

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

ML 167

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Marktechpost

MARCH 22, 2024

Data scientists and engineers frequently collaborate on machine learning ML tasks, making incremental improvements, iteratively refining ML pipelines, and checking the model’s generalizability and robustness. To build a well-documented ML pipeline, data traceability is crucial.

Machine Learning 135

Machine Learning Explainability Categorization ETL 135

IBM Journey to AI blog

AUGUST 6, 2024

The decentralized nature of multi-cloud is a complex factor in visualizing and controlling data—and in cases of a breach, it simply takes longer to gather information, investigate and activate the cloud provider’s support to contain the breach. Think about securing training data by protecting it from theft and manipulation.

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Marktechpost

MARCH 12, 2024

Even among datasets that include the same subject matter, there is no standard layout of files or data formats. This obstacle lowers productivity through machine learning development—from data discovery to model training. Additionally, it makes it harder to create essential tools for dealing with huge datasets.

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IBM Journey to AI blog

JANUARY 18, 2023

It can include technologies that range from Oracle, Teradata and Apache Hadoop to Snowflake on Azure, RedShift on AWS or MS SQL in the on-premises data center, to name just a few. All phases of the data-information lifecycle. The data fabric embraces all phases of the data-information-insight lifecycle.

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AWS Machine Learning Blog

AUGUST 22, 2024

Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry. Verisk’s Discovery Navigator product is a leading medical record review platform designed for property and casualty claims professionals, with applications to any industry that manages large volumes of medical records.

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AWS Machine Learning Blog

MAY 31, 2024

The General Data Protection Regulation (GDPR) right to be forgotten, also known as the right to erasure, gives individuals the right to request the deletion of their personally identifiable information (PII) data held by organizations. Example: customer information pertaining to the email address art@venere.org.

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Google Research AI blog

FEBRUARY 28, 2023

For one example, in the United States a recent new policy requires free and equitable access to outcomes of all federally funded research, including data and statistical information along with publications.

Metadata 116

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IBM Journey to AI blog

JULY 3, 2024

Your data strategy should incorporate databases designed with open and integrated components, allowing for seamless unification and access to data for advanced analytics and AI applications within a data platform. This enables your organization to extract valuable insights and drive informed decision-making.

Data Quality 112

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Attivio

JUNE 8, 2015

June 8, 2015: Attivio ( www.attivio.com ), the Data Dexterity Company, today announced Attivio 5, the next generation of its software platform. And anecdotal evidence supports a similar 80% effort within data integration just to identify and profile data sources.” [1] Newton, Mass.,

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Business Intelligence Big Data Data Discovery Data Scientist 40

Pickl AI

OCTOBER 14, 2024

Introduction Data Analysis transforms raw data into valuable insights that drive informed decisions. It systematically examines data to uncover patterns, trends, and relationships that help organisations solve problems and make strategic choices. Data Analysis plays a crucial role in filtering and structuring this data.

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DataRobot Blog

APRIL 1, 2018

In Rita Sallam’s July 27 research, Augmented Analytics , she writes that “the rise of self-service visual-bases data discovery stimulated the first wave of transition from centrally provisioned traditional BI to decentralized data discovery.” We agree with that.

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ODSC - Open Data Science

JUNE 2, 2023

By having all users take part in the analytical flow, companies can ensure relevant and accurate information reaches decision-makers timely and effectively. Resiliency to disruption is necessary to gain trust and keep information at the forefront. Win-win, right? So where do you fit into the BI equation?

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Pickl AI

JUNE 13, 2024

This blog explores what data classification is, its benefits, and different approaches to categorize your information. Discover how to protect sensitive data, ensure compliance, and streamline data management. Introduction In today’s digital age, information is king. Internal: Data for internal use only (e.g.,

Categorization 52

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ODSC - Open Data Science

FEBRUARY 13, 2024

Its goal is to reveal possible data compromise early. How does DSPM help you prevent data breaches? First, It Discovers The Data “You can’t protect what you can’t see” is the common mantra in information security. Discovering what kind of data you have is DSPM’s starting point. They have to be quick to respond.

Data Science 52

Data Science Data Discovery Machine Learning Automation 52

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making. It supports both batch and real-time processing.

Data Ingestion 52

Data Ingestion ETL Data Quality Data Integration 52

Pickl AI

JUNE 11, 2024

Summary: Exploratory Data Analysis (EDA) uses visualizations to uncover patterns and trends in your data. Histograms, scatter plots, and charts reveal relationships and outliers, helping you understand your data and make informed decisions. This can foster deeper understanding and promote data discovery.

Data Analysis 52

Data Analysis Categorization Data Science Data Discovery 52

ODSC - Open Data Science

OCTOBER 25, 2024

Delphina Demo: AI-powered Data Scientist Jeremy Hermann | Co-founder at Delphina | Delphina.Ai In this demo, you’ll see how Delphina’s AI-powered “junior” data scientist can transform the data science workflow, automating labor-intensive tasks like data discovery, transformation, and model building.

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Data Scientist Software Engineer Machine Learning Automation 52

The MLOps Blog

MAY 17, 2023

As a result, the final repository contains clean, complete, and trustworthy data to be used further without amendments. Coupler ETL architecture often includes a diagram like the one above that outlines the flow of information in the ETL pipeline from data sources to the final destination.

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Pickl AI

JULY 6, 2023

These work together to enable efficient data processing and analysis: · Hive Metastore It is a central repository that stores metadata about Hive’s tables, partitions, and schemas. By leveraging its features and understanding its limitations, businesses can unlock the full potential of their data.

Big Data 52

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Heartbeat

DECEMBER 21, 2023

Uncovering the Power of Comet Across the Data Science Journey Photo by Nguyen Le Viet Anh on Unsplash Machine learning (ML) projects are usually complicated and include several stages, from data discovery to model implementation. There are some other functions as well that can be helpful for Data Exploration.

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Pickl AI

OCTOBER 10, 2023

This involves implementing data validation processes, data cleansing routines, and quality checks to eliminate errors, inaccuracies, or inconsistencies. Reliable data is essential for making informed decisions and conducting meaningful analyses. For more information on this, connect with Pickl.AI

Data Quality 52

Data Quality Machine Learning Data Science Data Integration 52

Marktechpost

JULY 18, 2023

An online SQL client, a cloud data backup tool, and an OData server-as-a-service option are also included. Voracity supports hundreds of data sources and immediately feeds BI and visualization targets as a “production analytic platform.” The IBM product Infosphere Information Server was created in 2008.

ETL 52

ETL Data Integration Business Intelligence Automation 52

Snorkel AI

JULY 5, 2023

Generally, data is produced by one team, and then for that to be discoverable and useful for another team, it can be a daunting task for most organizations. Even larger, more established organizations struggle with data discovery and usage. It covers the training pipeline and the serving or inference process as well.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

Generally, data is produced by one team, and then for that to be discoverable and useful for another team, it can be a daunting task for most organizations. Even larger, more established organizations struggle with data discovery and usage. It covers the training pipeline and the serving or inference process as well.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Snorkel AI

JULY 5, 2023

Generally, data is produced by one team, and then for that to be discoverable and useful for another team, it can be a daunting task for most organizations. Even larger, more established organizations struggle with data discovery and usage. It covers the training pipeline and the serving or inference process as well.

Large Language Models 52

Large Language Models Metadata Machine Learning AI 52

Unite.AI

AUGUST 7, 2024

This is achieved by automatically scanning an organization’s data landscape (SaaS, IaaS, cloud data lakes and warehouses, etc.) and getting granular insights into all the sensitive information and AI systems. Can you discuss the role of AI in Securiti’s platform and how it enhances data security and governance?

Data Discovery 147

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ML @ CMU

MARCH 24, 2023

Algorithmic methods that find clusters of data with high error have also shown promise for surfacing problematic behaviors. Data discovery and generation. Having high-quality, representative data remains a persistent obstacle for behavioral evaluation. Fixing behaviors.

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AI Development AI Developer Metadata Python 144

IBM Journey to AI blog

MAY 17, 2024

This can leave decision-makers feeling unsupported, as they need more than just data; they need insights that directly inform action. The “unknown unknowns” A significant barrier to BI adoption is the challenge of not knowing what questions to ask or what data might be relevant.

Business Intelligence 253

Business Intelligence Data Analysis Continuous Learning Data Discovery 253

Marktechpost

AUGUST 26, 2024

Data discovery has become increasingly challenging due to the proliferation of easily accessible data analysis tools and low-cost cloud storage. While these advancements have democratized data access, they have also led to less structured data stores and a rapid expansion of derived artifacts in enterprise environments.

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Data Discovery Metadata Data Analysis Algorithm 56

Marktechpost

NOVEMBER 4, 2024

In today’s data-driven world, data analysts play a crucial role in various domains. Businesses use data extensively to inform strategy, enhance operations, and obtain a competitive edge. Tableau is a cost-effective option for businesses concentrating on data-driven storytelling and visualization.

Data Analysis 81

Data Analysis Machine Learning Data Science Python 81

Marktechpost

NOVEMBER 1, 2024

Tableau Tableau is well known for its user-friendly data visualization features, which let users make dynamic, interactive dashboards without knowing any code. Ask Data, an AI-powered element of the tool, allows users to ask questions in natural language and instantly get visual insights.

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IBM Journey to AI blog

AUGUST 3, 2023

The risks include non-compliance to regulatory requirements and can lead to excessive hoarding of sensitive data when it’s not necessary. It’s both a data security and privacy issue. Adopting a zero-trust approach to data security and privacy means never assuming anyone or anything is trustworthy.

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DataRobot Blog

OCTOBER 3, 2017

Many announcements at Strata centered on product integrations, with vendors closing the loop and turning tools into solutions, most notably: A Paxata-HDInsight solution demo, where Paxata showcased the general availability of its Adaptive Information Platform for Microsoft Azure.

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