CIO Business Intelligence

MARCH 21, 2022

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. Data scientist job description. Semi-structured data falls between the two.

Unstructured Data 137

Unstructured Data Data Analytics Analytics Data Science 137

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

JULY 16, 2024

The second is “Where is this data?” Let’s explore some of the common data types that present challenges – and how to solve them for AI. Structured data Structured data is often the first type of data that comes to mind when people think about databases.

Unstructured Data 105

Unstructured Data Structured Data Machine Learning Enterprise 105

Analytics Vidhya

AUGUST 26, 2021

This article was published as a part of the Data Science Blogathon The intersection of medicine and data science has always been relevant; perhaps the most obvious example is the implementation of neural networks in deep learning. As data science and machine learning advance, so will medicine, but the opposite is also true.

Deep Learning 284

Deep Learning Machine Learning Data Science Publishing 284

Sisense

APRIL 26, 2020

Different types of information are more suited to being stored in a structured or unstructured format. Read on to explore more about structured vs unstructured data, why the difference between structured and unstructured data matters, and how cloud data warehouses deal with them both.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Data Lake 178

Data Lake Unstructured Data Management Analytics 178

AWS Big Data

FEBRUARY 29, 2024

The need for an end-to-end strategy for data management and data governance at every step of the journey—from ingesting, storing, and querying data to analyzing, visualizing, and running artificial intelligence (AI) and machine learning (ML) models—continues to be of paramount importance for enterprises.

Data Governance 106

Data Governance Unstructured Data Metadata Data Lake 106

Smart Data Collective

FEBRUARY 3, 2021

Big data algorithms that understand these principles can use them to forecast the direction of the stock market. Automatic trading, which hugely relies on artificial intelligence and bots, and trading that operates on machine learning are eliminating the human emotion factor from all this.

Big Data 140

Big Data Marketing Data Analytics Analytics 140

CIO Business Intelligence

SEPTEMBER 19, 2024

“As we do that, we’re learning constantly, and that learning allows us to take what otherwise a standard LLM might not know, and then season it with information that is specific to that enterprise so that we can translate their technical speak into something that is understandable.”

Data Governance 123

Data Governance Metadata Unstructured Data Structured Data 123

CIO Business Intelligence

MARCH 9, 2022

As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. Newer data lakes are highly scalable and can ingest structured and semi-structured data along with unstructured data like text, images, video, and audio.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

CIO Business Intelligence

SEPTEMBER 12, 2024

For most organizations, the effective use of AI is essential for future viability and, in turn, requires large amounts of accurate and accessible data. Across industries, 78 % of executives rank scaling AI and machine learning (ML) use cases to create business value as their top priority over the next three years.

Unstructured Data 119

Unstructured Data Data Quality Structured Data Machine Learning 119

Analytics Vidhya

JULY 8, 2023

But what does it take to clear the rigorous data science interview process?

Data Science 222

Data Science Statistics Machine Learning Analytics 222

Cloudera

JUNE 11, 2024

By leveraging an organization’s proprietary data, GenAI models can produce highly relevant and customized outputs that align with the business’s specific needs and objectives. Structured data is highly organized and formatted in a way that makes it easily searchable in databases and data warehouses.

Enterprise 95

Enterprise Unstructured Data Contextual Data Data-driven 95

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. Today, 60% to 70% of Rocket’s workloads run on the cloud, with more than 95% of those workloads in AWS.

Data Lake 134

Data Lake Machine Learning Data Warehouse Unstructured Data 134

Domino Data Lab

AUGUST 9, 2021

Before selecting a tool, you should first know your end goal – machine learning or deep learning. Machine learning identifies patterns in data using algorithms that are primarily based on traditional methods of statistical learning. It’s most helpful in analyzing structured data.

Modeling 111

Modeling Deep Learning Machine Learning Statistics 111

CIO Business Intelligence

OCTOBER 2, 2024

A “state-of-the-art” data and analytics enablement platform can vastly improve identity resolution, helping to prevent fraud. Ideally, it will link structured data like traditional offline identities with unstructured data, including behavioral information, device properties, and other factors.

Analytics 115

Analytics Unstructured Data Interactive Data Governance 115

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. Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

Unstructured Data 99

Unstructured Data Data Warehouse Structured Data Testing 99

IBM Big Data Hub

JULY 6, 2023

To keep up with the pace of consumer expectations, companies are relying more heavily on machine learning algorithms to make things easier. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other? Machine learning is a subset of AI.

Deep Learning 56

Deep Learning Machine Learning Unstructured Data Modeling 56

CIO Business Intelligence

FEBRUARY 16, 2023

My vision is that I can give the keys to my businesses to manage their data and run their data on their own, as opposed to the Data & Tech team being at the center and helping them out,” says Iyengar, director of Data & Tech at Straumann Group North America. The company’s Findability.ai

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

Timo Elliott

JANUARY 22, 2019

Machine learning everywhere. We’ve reached the third great wave of analytics, after semantic-layer business intelligence platforms in the 90s and data discovery in the 2000s. Augmented analytics platforms based on cloud technology and machine learning are breaking down the longest-standing barriers to analytics success.

Analytics 96

Analytics Machine Learning Unstructured Data Digital Transformation 96

AWS Big Data

SEPTEMBER 12, 2024

AWS services such as Amazon Neptune and Amazon OpenSearch Service form part of their data and analytics pipelines, and AWS Batch is used for long-running data and machine learning (ML) processing tasks. Clinical documents often contain a mix of structured and unstructured data.

Unstructured Data 106

Unstructured Data Metadata Consulting Machine Learning 106

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 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

BizAcuity

MARCH 29, 2019

Data lakes are centralized repositories that can store all structured and unstructured data at any desired scale. The power of the data lake lies in the fact that it often is a cost-effective way to store data. In the future of healthcare, data lake is a prominent component, growing across the enterprise.

Data Lake 102

Data Lake Unstructured Data Cost-Benefit Data Quality 102

CIO Business Intelligence

AUGUST 21, 2024

Gartner estimates unstructured content makes up 80% to 90% of all new data and is growing three times faster than structured data 1. The ability to effectively wrangle all that data can have a profound, positive impact on numerous document-intensive processes across enterprises. 20, 2023.

Insurance 122

Insurance Unstructured Data Structured Data Enterprise 122

Cloudera

MAY 14, 2024

This form of hybrid also goes a level deeper than one may find in a standard hybrid cloud, accounting for the entirety of the data lifecycle, whether that’s the point of ingestion, warehousing, or machine learning—even when that end-to-end data lifecycle is split between entirely different environments.

Data Architecture 101

Data Architecture Data Governance Unstructured Data Structured Data 101

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. Unstructured data interpretation: Unstructured data can often contain untapped insights.

Unstructured Data 84

Unstructured Data Data-driven ROI Machine Learning 84

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 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

CIO Business Intelligence

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). Under Guadagno, the Deerfield, Ill. That’s how we got here.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

Jet Global

SEPTEMBER 4, 2020

Data lakes serve a fundamentally different purpose than data warehouses, in the sense that they are optimized for extremely high volumes of data that may or may not be structured. There are virtually no rules about what such data looks like. It is unstructured.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

Smart Data Collective

SEPTEMBER 26, 2019

For example, you can organize an employee table in a database in a structured manner to capture the employee’s details, job positions, salary, etc. Unstructured. Unstructured data lacks a specific format or structure. As a result, processing and analyzing unstructured data is super-difficult and time-consuming.

Big Data 81

Big Data Software Unstructured Data Data Integration 81

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 114

IT Data Architecture Unstructured Data Big Data 114

bridgei2i

FEBRUARY 28, 2020

The rise of new kinds of data and analysis techniques from AI to machine learning that is actually driving the decisions behind the systems that can enable the so-called transformations. With AI, apart from the quantitative data, unstructured data systems can be assessed for risk management.

Risk Management 78

Risk Management Unstructured Data Machine Learning Digital Transformation 78

Jet Global

NOVEMBER 5, 2020

They are designed for enormous volumes of information, including semi-structured and unstructured data. Unstructured data could include things like social media posts, online reviews, and comments recorded by a customer service rep, for example. Data lakes move that step to the end of the process.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Ontotext

OCTOBER 19, 2023

In order to create an interoperable health data record, we should be able to integrate personal health data (which comes in various formats and structures and varying quality) into a shareable format with other systems and individuals. We are planning to develop or use AI-based tools for each of these problems.

Unstructured Data 64

Unstructured Data Structured Data Publishing Machine Learning 64

IBM Big Data Hub

JANUARY 10, 2024

AI operates on three fundamental components: data, algorithms and computing power. Data: AI systems learn and make decisions based on data, and they require large quantities of data to train effectively, especially in the case of machine learning (ML) models.

Unstructured Data 75

Unstructured Data Deep Learning Cost-Benefit Machine Learning 75

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 97

IT Data Architecture Unstructured Data Big Data 97