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 141

Unstructured Data Optimization Data-driven Strategy 141

CIO Business Intelligence

FEBRUARY 20, 2024

Data remains siloed in facilities, departments, and systems –and between IT and OT networks (according to a report by The Manufacturer , just 23% of businesses have achieved more than a basic level of IT and OT convergence). Denso uses AI to verify the structuring of unstructured data from across its organisation.

Data Architecture 86

Data Architecture Unstructured Data Manufacturing IT 86

CIO Business Intelligence

MARCH 21, 2022

What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Semi-structured data falls between the two.

Unstructured Data 134

Unstructured Data Data Analytics Analytics Structured Data 134

DataKitchen

FEBRUARY 27, 2024

Your LLM Needs a Data Journey: A Comprehensive Guide for Data Engineers The rise of Large Language Models (LLMs) such as GPT-4 marks a transformative era in artificial intelligence, heralding new possibilities and challenges in equal measure. In this context, multi-tool Data Journey observability becomes crucial.

Data Quality 120

Data Quality Unstructured Data Testing Modeling 120

IBM Big Data Hub

NOVEMBER 29, 2023

Non-symbolic AI can be useful for transforming unstructured data into organized, meaningful information. This helps to simplify data analysis and enable informed decision-making. Events as fuel for AI Models: Artificial intelligence models rely on big data to refine the effectiveness of their capabilities.

Unstructured Data 90

Unstructured Data Data-driven ROI Machine Learning 90

Smart Data Collective

AUGUST 28, 2021

Data Warehouses and Data Lakes in a Nutshell. A data warehouse is used as a central storage space for large amounts of structured data coming from various sources. On the other hand, data lakes are flexible storages used to store unstructured, semi-structured, or structured raw data.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Structured Data 140

CIO Business Intelligence

MARCH 29, 2024

That’s why Rocket Mortgage has been a vigorous implementor of machine learning and AI technologies — and why CIO Brian Woodring emphasizes a “human in the loop” AI strategy that will not be pinned down to any one generative AI model. Despite being primarily an AWS shop, Rocket has taken a model-agnostic approach to generative AI platforms.

Data Lake 118

Data Lake Machine Learning Data Warehouse Unstructured Data 118

CIO Business Intelligence

APRIL 25, 2024

“The challenge that a lot of our customers have is that requires you to copy that data, store it in Salesforce; you have to create a place to store it; you have to create an object or field in which to store it; and then you have to maintain that pipeline of data synchronization and make sure that data is updated,” Carlson said.

Data Integration 88

Data Integration Data Lake Metadata Data Warehouse 88

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

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 113

Cost-Benefit Unstructured Data Modeling Structured Data 113

Ontotext

OCTOBER 19, 2023

We need to solve many problems, including deduplication of data that refers to the same entity, extracting structured data within narratives in different languages, as well as mapping them to a common and international ontology. Cleaning and integrating this data to create a unified and accurate patient profile is essential.

Unstructured Data 64

Unstructured Data Structured Data Publishing Machine Learning 64

Ontotext

JULY 20, 2023

With our technology we can cover most use cases in one go, our platform is data agnostic and can do text and speech in different languages. Most importantly, our knowledge modeling is done with knowledge graphs , which enables us to merge different data types and enable answering complex questions.

Manufacturing 52

Manufacturing Unstructured Data Structured Data Modeling 52

CIO Business Intelligence

FEBRUARY 16, 2023

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

Unstructured Data 102

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 102

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

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. When data is stored in a modern, accessible repository, organizations gain newfound capabilities. Preserve/Dispose.

Unstructured Data 52

Unstructured Data Data Lake Business Objectives Metadata 52

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 88

Data Lake Unstructured Data Management Modeling 88

Ontotext

MAY 25, 2023

Click To Tweet Knowledge Graphs and Large Language Models (LLM): BFF Forever The rise of ChatGPT and other Large Language Models (LLM) has undoubtedly impacted the field of knowledge graphs. We saw presentations showing the potential for knowledge graphs and LLM to complement each other.

Machine Learning 52

Machine Learning Structured Data Unstructured Data Predictive Modeling 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

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. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent.

Unstructured Data 117

Unstructured Data Metadata Management Analytics 117

IBM Big Data Hub

APRIL 18, 2023

” Pioneering use of unstructured text data For over a decade, IBM has been gathering insight from unstructured data (such as that used in large language models) to provide real-time insight to its sports and entertainment clients and to enhance predictive analysis.

Recreation/Entertainment 76

Recreation/Entertainment Broadcasting Unstructured Data Consulting 76

Jet Global

NOVEMBER 5, 2020

That stands for “bring your own database,” and it refers to a model in which core ERP data are replicated to a separate standalone database used exclusively for reporting. OLAP reporting based on a data warehouse model is a well-proven solution for companies with robust reporting requirements.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

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 81

Experimentation Data Warehouse Dashboards Visualization 81

Analytics Vidhya

JULY 25, 2022

Machine Learning is the method of teaching computer programs to do a specific task accurately (essentially a prediction) by training a predictive model using various statistical algorithms leveraging data. Introduction Let’s have a simple overview of what Machine Learning is. Source: [link] For […].

Machine Learning 249

Machine Learning Predictive Modeling Statistics Data Science 249

Cloudera

JUNE 7, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 108

IT Data Architecture Unstructured Data Big Data 108

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

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

CIO Business Intelligence

JUNE 23, 2022

We live in a hybrid data world. In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 81

IT Data Architecture Unstructured Data Big Data 81

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

Ontotext

JANUARY 6, 2021

A knowledge graph can be used as a database because it structures data that can be queried such as through a query language like SPARQL. Ontotext worked with a global research-based biopharmaceutical company to solve the problem of inefficient search across dispersed and vast sources of unstructured data.

Metadata 59

Metadata Unstructured Data Cost-Benefit Enterprise 59

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 56

Data mining Machine Learning Deep Learning Marketing 56

CIO Business Intelligence

JUNE 28, 2022

For example, they may not be easy to apply or simple to comprehend but thanks to bench scientists and mathematicians alike, companies now have a range of logistical frameworks for analyzing data and coming to conclusions. More importantly, we also have statistical models that draw error bars that delineate the limits of our analysis.

Management 134

Management Internet of Things Statistics Data-driven 134

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Ontotext

NOVEMBER 2, 2023

The pathway forward doesn’t require ripping everything out but building a semantic “graph” layer across data to connect the dots and restore context. However, it will take effort to formalize a shared semantic model that can be mapped to data assets, and turn unstructured data into a format that can be mined for insight.

IT 69

IT Cost-Benefit Data-driven Technology 69

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

FineReport

MARCH 7, 2024

However, due to regulatory controls on sensitive data like phone numbers and technical challenges in cross-platform integration of Internet and mobile reporting data, our current matching rates are relatively low, reaching around 20% in ideal scenarios, excluding telecom data.

Dashboards 52

Dashboards Reporting Advertising Statistics 52

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Pre-Check: Data Lake Cluster.

Data Lake 68

Data Lake Metadata Unstructured Data Management 68

Domino Data Lab

AUGUST 9, 2021

For a model-driven enterprise, having access to the appropriate tools can mean the difference between operating at a loss with a string of late projects lingering ahead of you or exceeding productivity and profitability forecasts. What Are Modeling Tools? Importance of Modeling Tools. Types of Modeling Tools.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111