IBM Big Data Hub

AUGUST 1, 2023

True to their name, generative AI models generate text, images, code , or other responses based on a user’s prompt. But what makes the generative functionality of these models—and, ultimately, their benefits to the organization—possible? That’s where the foundation model enters the picture.

Modeling 56

Modeling Cost-Benefit Data Lake Machine Learning 56

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. Foundation models: The power of curated datasets Foundation models , also known as “transformers,” are modern, large-scale AI models trained on large amounts of raw, unlabeled data.

Risk 72

Risk Modeling Management Metadata 72

AWS Big Data

MAY 28, 2024

Large language models (LLMs) such as Anthropic Claude and Amazon Titan have the potential to drive automation across various business processes by processing both structured and unstructured data. This would allow analysts to process the documents to develop investment recommendations faster and more efficiently.

Unstructured Data 88

Unstructured Data Structured Data Data Warehouse Testing 88

IBM Big Data Hub

APRIL 15, 2024

Or we create a data lake, which quickly degenerates to a data swamp. Additionally, these accelerators are pre-integrated with various cloud AI services and recommend the best LLM (large language model) for their domain. Generative AI can create foundation models for assets.

Manufacturing 95

Manufacturing Contextual Data Knowledge Discovery Data Lake 95

AWS Big Data

FEBRUARY 29, 2024

Data is your generative AI differentiator, and a successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Data governance is a critical building block across all these approaches, and we see two emerging areas of focus.

Data Governance 97

Data Governance Unstructured Data Metadata Data Lake 97

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 102

Data Lake Data Warehouse Management Risk 102

Cloudera

MAY 23, 2024

In modern enterprises, the exponential growth of data means organizational knowledge is distributed across multiple formats, ranging from structured data stores such as data warehouses to multi-format data stores like data lakes. The image above demonstrates a KMS built using the llama3 model from Meta.

Management 78

Management Metrics Data Processing Data Lake 78

CIO Business Intelligence

APRIL 1, 2024

Capturing the “as-is” state of your environment, you’ll develop topology diagrams and document information on your technical systems. Ensure that data is cleansed, consistent, and centrally stored, ideally in a data lake. Data preparation, including anonymizing, labeling, and normalizing data across sources, is key.

Data Lake 124

Data Lake Consulting Uncertainty Risk 124

Paul Blogs on BI

MAY 13, 2024

One such feature that has recently stood out for me is “Web Intelligence as a data source”. allows you to create a master Webi document and then place a universe on top of this document to enable users to create child reports, dashboards and extracts from this one master document. With the latest service pack of BI 4.3,

Data Warehouse 52

Data Warehouse Data Lake Reporting Dashboards 52

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 81

Data Lake Data Warehouse Data-driven Optimization 81

erwin

SEPTEMBER 3, 2020

Data governance provides time-sensitive, current-state architecture information with a high level of quality. It documents your data assets from end to end for business understanding and clear data lineage with traceability. Automating Data Governance and Enterprise Architecture.

Data Governance 144

Data Governance Enterprise Risk Data Lake 144

AWS Big Data

SEPTEMBER 26, 2023

AWS Lake Formation helps you centrally govern, secure, and globally share data for analytics and machine learning. With Lake Formation, you can manage access control for your data lake data in Amazon Simple Storage Service (Amazon S3 ) and its metadata in AWS Glue Data Catalog in one place with familiar database-style features.

Data Lake 65

Data Lake Metadata Management Modeling 65

Jet Global

OCTOBER 22, 2020

As the Microsoft Dynamics ERP products transition to a cloud-first model, Microsoft has positioned Power BI as the future of business intelligence for its Dynamics family of products. OLAP Cubes vs. Tabular Models. Let’s begin with an overview of how data analytics works for most business applications.

Modeling 52

Modeling OLAP Reporting Sales 52

CIO Business Intelligence

APRIL 9, 2024

Previously head of cybersecurity at Ingersoll-Rand, Melby started developing neural networks and machine learning models more than a decade ago. I was literally just waiting for commercial availability [of LLMs] but [services] like Azure Machine Learning made it so you could easily apply it to your data.

Digital Transformation 89

Digital Transformation Machine Learning Data Lake Software 89

datapine

APRIL 15, 2020

Working software over comprehensive documentation. Business intelligence is moving away from the traditional engineering model: analysis, design, construction, testing, and implementation. In the traditional model communication between developers and business users is not a priority. Finalize documentation, where necessary.

Business Intelligence 276

Business Intelligence Analytics Testing Dashboards 276

IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.” Lastly, watsonx.data pulls from live feeds.

Management 80

Management IT Machine Learning Metrics 80

Smart Data Collective

AUGUST 17, 2022

A hybrid cloud system is a cloud deployment model combining different cloud types, using both an on-premise hardware solution and a public cloud. You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others.

Data Lake 108

Data Lake Insurance Data-driven Data Processing 108

AWS Big Data

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. Text, images, audio, and videos are common examples of unstructured data. The steps of the workflow are as follows: Integrated AI services extract data from the unstructured data.

Unstructured Data 121

Unstructured Data Metadata Management Analytics 121

Cloudera

JUNE 25, 2021

The Replication Manager support matrix is documented in our public docs. This blog post outlines detailed step by step instructions to perform Hive Replication from an on-prem CDH cluster to a CDP Public Cloud Data Lake. CDP Data Lake cluster versions – CM 7.4.0, CDP Data Lake cluster versions – CM 7.4.0,

Data Lake 71

Data Lake Metadata Unstructured Data Management 71

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

CIO Business Intelligence

MARCH 9, 2022

Despite the worldwide chaos, UAE national airline Etihad has managed to generate productivity gains and cost savings from insights using data science. Etihad began its data science journey with the Cloudera Data Platform and moved its data to the cloud to set up a data lake. Reem Alaya Lebhar. Talal Mufti.

Data Science 88

Data Science Data Lake Cost-Benefit Digital Transformation 88

CIO Business Intelligence

FEBRUARY 10, 2023

Deploying new data types for machine learning Mai-Lan Tomsen-Bukovec, vice president of foundational data services at AWS, sees the cloud giant’s enterprise customers deploying more unstructured data, as well as wider varieties of data sets, to inform the accuracy and training of ML models of late.

Unstructured Data 104

Unstructured Data Data Lake Machine Learning Enterprise 104

erwin

OCTOBER 8, 2020

But even with the “need for speed” to market, new applications must be modeled and documented for compliance, transparency and stakeholder literacy. The metadata-driven suite automatically finds, models, ingests, catalogs and governs cloud data assets. Subscribe to the erwin Expert Blog.

Data Governance 145

Data Governance Metadata Testing Data Lake 145

Domino Data Lab

JUNE 15, 2021

Over the next decade, the companies that will beat competitors will be “model-driven” businesses. These companies often undertake large data science efforts in order to shift from “data-driven” to “model-driven” operations, and to provide model-underpinned insights to the business. anomaly detection).

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

IBM Big Data Hub

MAY 9, 2023

The answer is that generative AI leverages recent advances in foundation models. Unlike traditional ML, where each new use case requires a new model to be designed and built using specific data, foundation models are trained on large amounts of unlabeled data, which can then be adapted to new scenarios and business applications.

Data Warehouse 107

Data Warehouse Machine Learning Cost-Benefit Metadata 107

Cloudera

NOVEMBER 18, 2021

By adopting a custom developed application based on the Cloudera ecosystem, Carrefour has combined the legacy systems into one platform which provides access to customer data in a single data lake. EVA unifies data from MTN’s different operator systems, creating a 360° view of subscribers.

Data Lake 76

Data Lake Cost-Benefit Digital Transformation Risk 76

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Cloudera

NOVEMBER 5, 2020

When you register an Environment in CDP, a Data Lake is automatically deployed for that environment. Data Lake security and governance is managed by a shared set of services running within a Data Lake cluster. Their entire business model is premised on secure sharing of data products.

Data Lake 72

Data Lake Data Warehouse Metadata Optimization 72

CIO Business Intelligence

SEPTEMBER 21, 2023

AI is now a board-level priority Last year, AI consisted of point solutions and niche applications that used ML to predict behaviors, find patterns, and spot anomalies in carefully curated data sets. Today’s foundational models are jacks-of-all-trades. All of PwC’s clients are having this discussion, he says. Then gen AI came out.

Enterprise 127

Enterprise Consulting Modeling Cost-Benefit 127

Cloudera

AUGUST 9, 2022

The DRRA focuses on describing how to think about reliability, resiliency, and recovery for the Cloudera Data Platform, and is a living document describing our collected learning across the platform and across customers. . Automating the healing, recovery, scaling, and rebalancing of core data services such as our Operational Database.

Data Lake 77

Data Lake Data Warehouse Data-driven IoT 77

Cloudera

JANUARY 30, 2023

Have you ever considered how much data a single person generates in a day? Every web document, scanned document, email, social media post, and media download? One estimate states that “ on average, people will produce 463 exabytes of data per day by 2025.” Now consider that the federal government has approximately 2.8

IoT 82

IoT Data Architecture Data Lake Machine Learning 82

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 78

Cost-Benefit Metadata Data Governance Modeling 78

Ontotext

FEBRUARY 12, 2024

This calls for additional planning, documentation, and testing. A data mesh will likely require more engineers to get started, so a critical mass is needed for successful adoption. Each team should be accountable for providing their prepared data sets to downstream systems. For instance, JPMorgan Chase & Co.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

DataRobot Blog

MARCH 7, 2023

Organizations that want to prove the value of AI by developing, deploying, and managing machine learning models at scale can now do so quickly using the DataRobot AI Platform on Microsoft Azure. Models trained in DataRobot can also be easily deployed to Azure Machine Learning, allowing users to host models easier in a secure way.

Data-driven 59

Data-driven Machine Learning Experimentation Data Lake 59

IBM Big Data Hub

JULY 27, 2023

Precisely conducted a study that found that within enterprises, data scientists spend 80% of their time cleaning, integrating and preparing data , dealing with many formats, including documents, images, and videos. Overall placing emphasis on establishing a trusted and integrated data platform for AI.

Management 55

Management Enterprise Modeling Data Quality 55

Cloudera

APRIL 22, 2021

Storage plays one of the most important roles in the data platforms strategy, it provides the basis for all compute engines and applications to be built on top of it. Businesses are also looking to move to a scale-out storage model that provides dense storages along with reliability, scalability, and performance.

Data Lake 100

Data Lake Cost-Benefit Testing Metadata 100

CIO Business Intelligence

DECEMBER 4, 2023

Tomorrow’s market leaders will recognize how to curate and enrich the value of all assets, which will train AI models, generate insights, and drive automation. The ways modern data is used, processed, and analyzed are continuously evolving as machine learning technology becomes better at these tasks. Connect/Activate.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52