Analytics Vidhya

MAY 3, 2023

Introduction In the modern world, data science(DS) has emerged as one of the most sought-after careers. Fundamentally, it is the art of transforming unstructured data into a usable format and then drawing actionable insights from it.

Data Science 334

Data Science Unstructured Data Machine Learning Technology 334

KDnuggets

JANUARY 23, 2024

This week on KDnuggets: Here are five free university courses to help you get started in a data science career • Understand the unstructured data dilemma • And much, much more!

Unstructured Data 129

Unstructured Data Data Science 129

Analytics Vidhya

OCTOBER 17, 2022

This article was published as a part of the Data Science Blogathon. Introduction A data lake is a centralized repository for storing, processing, and securing massive amounts of structured, semi-structured, and unstructured data. It can store data in its native format and process any type of data, regardless of size.

Data Lake 322

Data Lake Unstructured Data Data Science Publishing 322

Analytics Vidhya

FEBRUARY 2, 2024

Introduction In the era of big data, organizations are inundated with vast amounts of unstructured textual data. The sheer volume and diversity of information present a significant challenge in extracting insights.

Unstructured Data 249

Unstructured Data Big Data Analytics Structured Data 249

Analytics Vidhya

JULY 26, 2022

This article was published as a part of the Data Science Blogathon. Introduction AWS Redshift is a powerful, petabyte-scale, highly managed cloud-based data warehousing solution. It processes and handles structured and unstructured data in exabytes (1018 bytes).

Unstructured Data 319

Unstructured Data Data Science Publishing Management 319

Analytics Vidhya

MAY 30, 2022

Azure Data Lake Storage is capable of storing large quantities of structured, semi-structured, and unstructured data in […]. The post Introduction to Azure Data Lake Storage Gen2 appeared first on Analytics Vidhya. Introduction ADLS Gen2 The ADLS Gen2 service is built upon Azure Storage as its foundation.

Data Lake 311

Data Lake Unstructured Data Data Science Publishing 311

Analytics Vidhya

MARCH 16, 2021

ArticleVideo Book Introduction Deep learning techniques are popularly used for unstructured data such as text data or image data. And before working on any. The post How Images are stored in the computer? appeared first on Analytics Vidhya.

Unstructured Data 297

Unstructured Data Deep Learning Analytics 297

Analytics Vidhya

SEPTEMBER 13, 2021

This article was published as a part of the Data Science Blogathon Introduction Let’s look at a practical application of the supervised NLP fastText model for detecting sarcasm in news headlines. About 80% of all information is unstructured, and text is one of the most common types of unstructured data.

Unstructured Data 266

Unstructured Data Data Science Publishing Modeling 266

David Menninger's Analyst Perspectives

MARCH 30, 2020

I was recently asked to identify key modern data architecture trends. Data architectures have changed significantly to accommodate larger volumes of data as well as new types of data such as streaming and unstructured data. Here are some of the trends I see continuing to impact data architectures.

Data Architecture 292

Data Architecture Unstructured Data Data Lake Data Governance 292

KDnuggets

SEPTEMBER 24, 2024

Healthcare generates a vast amount of unstructured data, including clinical notes, patient messages, and research articles. This data contains valuable insights that can significantly improve patient care, but are difficult to include in traditional modeling techniques due to its unstructured format.

Unstructured Data 96

Unstructured Data Modeling IT 96

Analytics Vidhya

NOVEMBER 7, 2023

Introduction In the ever-evolving field of natural language processing and artificial intelligence, the ability to extract valuable insights from unstructured data sources, like scientific PDFs, has become increasingly critical.

Unstructured Data 252

Unstructured Data Modeling Analytics Technology 252

Analytics Vidhya

JANUARY 20, 2022

This article was published as a part of the Data Science Blogathon. Introduction In this article, I am going to explain, how can we use log parsing with Spark and Scala to get meaningful data from unstructured data. In my experience, after parsing a lot of logs from different sources, I have found no data is […].

Unstructured Data 286

Unstructured Data Data Science Publishing Analytics 286

Analytics Vidhya

SEPTEMBER 16, 2021

This article was published as a part of the Data Science Blogathon Introduction Analyzing texts is far more complicated than analyzing typical tabulated data (e.g. retail data) because texts fall under unstructured data. Different people express themselves quite differently when it comes to […].

Unstructured Data 240

Unstructured Data IT Data Science Publishing 240

Analytics Vidhya

OCTOBER 9, 2022

Introduction Textual data from social media posts, customer feedback, and reviews are valuable resources for any business. There is a host of useful information in such unstructured data that we can discover. Making sense of this unstructured data can help companies better understand […].

Unstructured Data 231

Unstructured Data Data Processing Data Science Publishing 231

Analytics Vidhya

AUGUST 25, 2023

Introduction Have you ever worked with unstructured data and thought of a way to detect the presence of tables in your document? To help you quickly process your documents?

Unstructured Data 229

Unstructured Data Analytics 229

Analytics Vidhya

AUGUST 31, 2022

This article was published as a part of the Data Science Blogathon. Introduction A data lake is a central data repository that allows us to store all of our structured and unstructured data on a large scale. The post A Detailed Introduction on Data Lakes and Delta Lakes appeared first on Analytics Vidhya.

Data Lake 243

Data Lake Unstructured Data Big Data Dashboards 243

Analytics Vidhya

MAY 4, 2022

Introduction Text Mining is also known as Text Data Mining or Text Analytics or is an artificial intelligence (AI) technology that uses natural language processing (NLP) to extract essential data from standard language text. It is a process to transform the unstructured data (text […].

Unstructured Data 241

Unstructured Data Data mining Data Science Publishing 241

Analytics Vidhya

MAY 24, 2022

This article was published as a part of the Data Science Blogathon. Introduction on Apache Hive Advanced big data tools must handle the massive amounts of structured and unstructured data generated daily. Data is not increasing only in terms of volume, but the variety and veracity of data are also growing.

Unstructured Data 233

Unstructured Data Big Data Data Science Publishing 233

Analytics Vidhya

OCTOBER 4, 2022

It takes unstructured data from multiple sources as input and stores it […]. Introduction Elasticsearch is a search platform with quick search capabilities. It is a Lucene-based search engine developed in Java but supports clients in various languages ​​such as Python, C#, Ruby, and PHP.

Unstructured Data 230

Unstructured Data Data Science Publishing Analytics 230

David Menninger's Analyst Perspectives

FEBRUARY 21, 2024

Unstructured data has been a significant factor in data lakes and analytics for some time. Twelve years ago, nearly a third of enterprises were working with large amounts of unstructured data. As I’ve pointed out previously , unstructured data is really a misnomer.

Unstructured Data 147

Unstructured Data Data Lake Enterprise Technology 147

O'Reilly on Data

NOVEMBER 19, 2024

Then connect the graph nodes and relations extracted from unstructured data sources, reusing the results of entity resolution to disambiguate terms within the domain context. Chunk your documents from unstructured data sources, as usual in GraphRAG. Let’s revisit the point about RAG borrowing from recommender systems.

Unstructured Data 255

Unstructured Data Structured Data Modeling Statistics 255

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

CIO Business Intelligence

JANUARY 24, 2024

“Similar to disaster recovery, business continuity, and information security, data strategy needs to be well thought out and defined to inform the rest, while providing a foundation from which to build a strong business.” Overlooking these data resources is a big mistake. What are the goals for leveraging unstructured data?”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

CIO Business Intelligence

OCTOBER 30, 2023

This infrastructure must be suited to handle extreme data growth, especially with unstructured data. An estimated 90% of the global datasphere is comprised of unstructured data 1. And it’s growing rapidly, estimated at 55-65% 2 year-over-year and three times faster than structured data.

Unstructured Data 143

Unstructured Data Optimization Data-driven Strategy 143

Rocket-Powered Data Science

MAY 21, 2024

One example of Pure Storage’s advantage in meeting AI’s data infrastructure requirements is demonstrated in their DirectFlash® Modules (DFMs), with an estimated lifespan of 10 years and with super-fast flash storage capacity of 75 terabytes (TB) now, to be followed up with a roadmap that is planning for capacities of 150TB, 300TB, and beyond.

Cost-Benefit 239

Cost-Benefit Unstructured Data Enterprise Technology 239

CIO Business Intelligence

AUGUST 21, 2024

Importantly, such tools can extract relevant data even from unstructured data – including PDFs, email, and even images – and accurately classify it, making it easy to find and use. Users can get business-specific answers, not generic answers like with consumer large language models, to make better-informed decisions.”

Management 134

Management Enterprise Unstructured Data Deep Learning 134

CIO Business Intelligence

JULY 16, 2024

Often the data resides in different databases, in diverse data centers, or in different clouds. Migrating the data into similar databases, and replicating data across multiple locations, provides the availability and speed required for AI applications. As much as 90% of an organization’s data is unstructured.

Unstructured Data 105

Unstructured Data Structured Data Machine Learning Enterprise 105

AWS Big Data

DECEMBER 19, 2024

Although Amazon DataZone automates subscription fulfillment for structured data assetssuch as data stored in Amazon Simple Storage Service (Amazon S3), cataloged with the AWS Glue Data Catalog , or stored in Amazon Redshift many organizations also rely heavily on unstructured data. Enter a name for the asset.

Publishing 75

Publishing Unstructured Data Metadata Data-driven 75

CIO Business Intelligence

OCTOBER 8, 2024

There’s a constant risk of data science projects failing by (for example) arriving at an insight that managers already figured out by hook or by crook—or correctly finding an insight that isn’t a business priority. And some of the biggest challenges to making the most of it are well-suited to the skills and mindset of data scientists.

Unstructured Data 117

Unstructured Data Data Science Uncertainty Sales 117

CIO Business Intelligence

JUNE 6, 2024

Vector database in Data Cloud becomes generally available To underpin enterprises’ own AI copilots, Salesforce is finally making generally available the vector database inside Data Cloud that it showcased in December , allowing them to combine structured and unstructured data from multiple locations in a way that AI models can use.

Sales 126

Sales Unstructured Data Enterprise Dashboards 126

CIO Business Intelligence

SEPTEMBER 12, 2024

Organizational data is diverse, massive in size, and exists in multiple formats (paper, images, audio, video, emails, and other types of unstructured data, as well as structured data) sprawled across locations and silos. Every AI journey begins with the right data foundation—arguably the most challenging step.

Unstructured Data 119

Unstructured Data Data Quality Structured Data Machine Learning 119

Cloudera

NOVEMBER 15, 2024

Enterprise organizations collect massive volumes of unstructured data, such as images, handwritten text, documents, and more. They also still capture much of this data through manual processes. The way to leverage this for business insight is to digitize that data.

Machine Learning 87

Machine Learning Unstructured Data Visualization Data Transformation 87

CIO Business Intelligence

NOVEMBER 22, 2024

Soumya Seetharam, CDIO at Corning, said the manufacturer has been on its data journey for a few years, with more than 70% of its business transaction data being ingested into a data platform. But that’s only structured data, she emphasized.

Unstructured Data 136

Unstructured Data Testing Modeling Enterprise 136

CIO Business Intelligence

DECEMBER 19, 2023

Improving search capabilities and addressing unstructured data processing challenges are key gaps for CIOs who want to deliver generative AI capabilities. But 99% also report technical challenges, listing integration (68%), data volume and cleansing (59%), and managing unstructured data (55% ) as the top three.

Digital Transformation 143

Digital Transformation Unstructured Data Machine Learning Risk Management 143

David Menninger's Analyst Perspectives

OCTOBER 31, 2024

It was not until the addition of open table formats— specifically Apache Hudi, Apache Iceberg and Delta Lake—that data lakes truly became capable of supporting multiple business intelligence (BI) projects as well as data science and even operational applications and, in doing so, began to evolve into data lakehouses.

Data Lake 130

Data Lake Unstructured Data Data Warehouse Software 130

CIO Business Intelligence

DECEMBER 10, 2024

Improving data quality and integrating new data sources to enrich customer and prospect data are vital for applying AI in marketing and sales. For example, many organizations have been centralizing customer data for some time, but gen AI can greatly enhance the ability to find patterns and signals in unstructured data sources.

Sales 142

Sales Metrics Data-driven Measurement 142

O'Reilly on Data

FEBRUARY 11, 2020

They’re still struggling with the basics: tagging and labeling data, creating (and managing) metadata, managing unstructured data, etc. Nearly one-quarter of respondents work as data scientists or analysts (see Figure 1). An additional 7% are data engineers. Some other common data quality issues (Figure 4)—e.g.,

Data Quality 308

Data Quality Metadata Data Governance Publishing 308