Alation

JUNE 2, 2022

These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. Currently, models are managed by modelers and by the software tools they use, which results in a patchwork of control, but not on an enterprise level. And until recently, such governance processes have been fragmented.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

IBM Big Data Hub

MARCH 29, 2024

But what if you could optimize even further? It may be the solution that finally breaks through dysfunctional silos of business units, applications, data and people, and moves beyond the constraints that have cost companies dearly. Challenge 2: Prepare data for AI models AI is only as trusted as the data that fuels it.

Management 91

Management Structured Data Modeling Data Governance 91

CIO Business Intelligence

OCTOBER 30, 2023

The key is to make data actionable for AI by implementing a comprehensive data management strategy. That’s because data is often siloed across on-premises, multiple clouds, and at the edge. Getting the right and optimal responses out of GenAI models requires fine-tuning with industry and company-specific data.

Unstructured Data 138

Unstructured Data Optimization Data-driven Strategy 138

IBM Big Data Hub

JULY 26, 2023

Discover the current and emerging use cases for AI in waste management, optimization, energy reduction and ESG reporting. AI solutions work by collecting asset performance data and feeding it into machine learning models, which can predict asset health and risk of failure.

Optimization 79

Optimization Manufacturing Cost-Benefit Reporting 79

IBM Big Data Hub

APRIL 9, 2024

” Watsonx.data lets organizations optimize workloads for different uses. Preparing and annotating data IBM watsonx.data helps organizations put their data to work, curating and preparing data for use in AI models and applications. ” Training and testing models The Masters digital team used watsonx.ai

Management 86

Management IT Machine Learning Metrics 86

CIO Business Intelligence

NOVEMBER 20, 2023

As a technology professional, seeing how artificial intelligence (AI) and generative AI/large language models can improve and save lives makes me think about the significant difference this can have on families and communities worldwide–including mine. Fox says it perfectly: “Family is not an important thing. It’s everything.”

Cost-Benefit 110

Cost-Benefit Unstructured Data Modeling Structured Data 110

CIO Business Intelligence

DECEMBER 13, 2023

Applications such as financial forecasting and customer relationship management brought tremendous benefits to early adopters, even though capabilities were constrained by the structured nature of the data they processed. have encouraged the creation of unstructured data.

Unstructured Data 93

Unstructured Data IoT Metadata Manufacturing 93

CIO Business Intelligence

NOVEMBER 14, 2022

A DSS leverages a combination of raw data, documents, personal knowledge, and/or business models to help users make decisions. The data sources used by a DSS could include relational data sources, cubes, data warehouses, electronic health records (EHRs), revenue projections, sales projections, and more.

Data mining 127

Data mining Data-driven Statistics OLAP 127

CIO Business Intelligence

MARCH 21, 2022

As such, a data scientist must have enough business domain expertise to translate company or departmental goals into data-based deliverables such as prediction engines, pattern detection analysis, optimization algorithms, and the like. Semi-structured data falls between the two.

Unstructured Data 132

Unstructured Data Data Analytics Analytics Structured Data 132

CIO Business Intelligence

APRIL 4, 2024

Like other CIOs, Katrina Redmond has been inundated with opportunities to deploy AI that promise to speed business and operations processes, and optimize workflows. The cost of implementing and running AI models can be quite high, so you have to be really careful in assessing the business worthiness of AI use cases,” he says.

Enterprise 128

Enterprise Cost-Benefit Forecasting Strategy 128

IBM Big Data Hub

NOVEMBER 29, 2023

Furthermore, AI algorithms’ capacity for recognizing patterns—by learning from your company’s unique historical data—can empower businesses to predict new trends and spot anomalies sooner and with low latency. Stream analytics can be used to help improve the speed and accuracy of models’ predictions.

Unstructured Data 92

Unstructured Data Data-driven ROI Machine Learning 92

CIO Business Intelligence

DECEMBER 4, 2023

Although less complex than the “4 Vs” of big data (velocity, veracity, volume, and variety), orienting to the variety and volume of a challenging puzzle is similar to what CIOs face with information management. Structure/Operationalize. When data is stored in a modern, accessible repository, organizations gain newfound capabilities.

Unstructured Data 52

Unstructured Data Data Lake Metadata Business Objectives 52

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 109

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 109

IBM Big Data Hub

JULY 19, 2023

The exponential leap in generative AI is already transforming many industries: optimizing workflows , helping human teams focus on value added tasks and accelerating time to market. Supply Chain: Demand forecasting, supply chain optimization, risk assessment and mitigation. Why IBM Consulting for generative AI on AWS?

Consulting 64

Consulting Machine Learning Manufacturing Optimization 64

Cloudera

NOVEMBER 15, 2021

In terms of representation, data can be broadly classified into two types: structured and unstructured. Structured data can be defined as data that can be stored in relational databases, and unstructured data as everything else. The challenges of data. Data curation.

Unstructured Data 86

Unstructured Data Recreation/Entertainment Structured Data Reporting 86

CIO Business Intelligence

JANUARY 24, 2024

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

Data Strategy 134

Data Strategy Strategy Unstructured Data Data Governance 134

Octopai

MARCH 22, 2023

Cost: Snowflake’s pricing model is based on usage, which means you only pay for what you use. This can be more cost-effective than traditional data warehousing solutions that require a significant upfront investment. Support for multiple data structures.

Cost-Benefit 78

Cost-Benefit Data Warehouse Unstructured Data Optimization 78

CIO Business Intelligence

FEBRUARY 16, 2023

Hence the drive to provide ML as a service to the Data & Tech team’s internal customers. All they would have to do is just build their model and run with it,” he says. That step, primarily undertaken by developers and data architects, established data governance and data integration. The offensive side?

Unstructured Data 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

Sisense

APRIL 26, 2020

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Cloudera

SEPTEMBER 17, 2020

They were not able to quickly and easily query and analyze huge amounts of data as required. They also needed to combine text or other unstructured data with structured data and visualize the results in the same dashboards. Query large-sized data without loading data back and forth and incurring twice the cost.

Experimentation 80

Experimentation Data Warehouse Dashboards Visualization 80

IBM Big Data Hub

AUGUST 28, 2023

Text mining —also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP) , artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data.

Data mining 57

Data mining Machine Learning Deep Learning Marketing 57

AWS Big Data

MARCH 25, 2024

Foundation models (FMs) are large machine learning (ML) models trained on a broad spectrum of unlabeled and generalized datasets. This scale and general-purpose adaptability are what makes FMs different from traditional ML models. FMs are multimodal; they work with different data types such as text, video, audio, and images.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

CDW Research Hub

APRIL 20, 2020

Snowflake, a data warehouse built specifically for the cloud, is one popular option. Snowflake helps eliminate many of the common issues data professionals face because it supports structured and semi-structured data, scales massive concurrency without limit, and boasts secure, live data sharing.

Data Warehouse 52

Data Warehouse Consulting Data-driven Structured Data 52

CIO Business Intelligence

OCTOBER 25, 2023

The release of intellectual property and non-public information Generative AI tools can make it easy for well-meaning users to leak sensitive and confidential data. Once shared, this data can be fed into the data lakes used to train large language models (LLMs) and can be discovered by other users.

Enterprise 128

Enterprise Risk Manufacturing Finance 128

IBM Big Data Hub

JULY 5, 2022

Store and query more than just traditional structured data with multi-model capabilities. Seamlessly integrate Db2 with your existing data lake to easily query datasets residing in open data formats like Parquet, Avro and more. To learn more, visit IBM Db2 and our IBM data management page. .

Data Lake 96

Data Lake Data Warehouse Publishing Structured Data 96

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. Complete the implementation tasks such as data ingestion and performance testing.

Testing 98

Testing Data Warehouse Metrics Cost-Benefit 98

CIO Business Intelligence

MARCH 24, 2023

It encompasses the people, processes, and technologies required to manage and protect data assets. The Data Management Association (DAMA) International defines it as the “planning, oversight, and control over management of data and the use of data and data-related sources.”

Data Governance 142

Data Governance Management Metadata Data Quality 142

Sisense

JUNE 8, 2020

Scalable cloud solutions: The future of data and analytics. Current, on-premises data platforms are not yielding optimal results for businesses. In short, cloud data warehouses and BI platforms have revolutionized the way organizations share and use data. Deeper insights from bigger data sets.

Data Warehouse 89

Data Warehouse Data-driven Dashboards Sales 89

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly. million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

AWS Big Data

JUNE 6, 2023

In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 56

Analytics Data Lake Testing Optimization 56

Ontotext

NOVEMBER 2, 2023

This is partly because integrating and moving data is not the only problem. The data itself is stored in a way that is not optimal for extracting insight. Unlocking additional value from data requires context, relationships, and structure, none of which are present in the way most organizations store their data today.

IT 69

IT Cost-Benefit Data-driven Technology 69

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. Open file formats enable analysis of the same Amazon S3 data using multiple processing and consumption layer components.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

Ontotext

SEPTEMBER 7, 2023

Doug : The reason I bring up ChatGPT and Large Language Models (LLM) is because they are helping graphs to get into mainstream adoption and for people to understand them. This gets back to ChatGPT and LLMs, where you’re trying to find patterns in data that wouldn’t necessarily be there in a traditional database model.

Technology 59

Technology Visualization Digital Transformation Management 59

Sisense

OCTOBER 6, 2020

And, as industrial, business, domestic, and personal Internet of Things devices become increasingly intelligent, they communicate with each other and share data to help calibrate performance and maximize efficiency. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company. This is quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

MARCH 13, 2024

You can modify the Lambda function to fetch additional vehicle information from a separate data store (for example, a DynamoDB table or a Customer Relationship Management system) to enrich the data, before storing the results in an S3 bucket. In this model, the Lambda function is invoked for each incoming event.

Analytics 94

Analytics IoT Metadata Internet of Things 94

Jet Global

SEPTEMBER 4, 2020

Consultants and developers familiar with the AX data model could query the database using any number of different tools, including a myriad of different report writers. Data entities are more secure and arguably easier to master than the relational database model, but one downside is there are lots of them!

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88