Knowledge Hut

APRIL 23, 2024

It highlights the importance of handling data in real-time or near-real-time to extract timely insights and enable swift actions. Regarding gathering in relation to velocity, it involves the pace at which data is collected or received. Customer data come in numerous formats. Consider both structured and unstructured data.

Big Data 52

Big Data Media Datasets Unstructured Data 52

Snowflake

SEPTEMBER 19, 2023

With all the hoopla around AI, there’s a lot to get up to speed on—especially the implications this technology has for data analytics. Ahmad has not only witnessed the emergence of AI in the data space but helped shape it throughout his career. AI unlocks new data use cases. Some takeaways?

Machine Learning 84

Machine Learning Unstructured Data Data Analytics Government 84

Knowledge Hut

NOVEMBER 3, 2023

MongoDB is a NoSQL database that’s been making rounds in the data science community. MongoDB’s unique architecture and features have secured it a place uniquely in data scientists’ toolboxes globally. Let us see where MongoDB for Data Science can help you.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Knowledge Hut

DECEMBER 21, 2023

This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed. To establish a career in big data, you need to be knowledgeable about some concepts, Hadoop being one of them.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

The Modern Data Company

MAY 10, 2023

In our previous post, The Pros and Cons of Leading Data Management and Storage Solutions , we untangled the differences among data lakes, data warehouses, data lakehouses, data hubs, and data operating systems. Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

Knowledge Hut

JANUARY 30, 2024

Goal To extract and transform data from its raw form into a structured format for analysis. To uncover hidden knowledge and meaningful patterns in data for decision-making. Data Source Typically starts with unprocessed or poorly structured data sources. Analyzing and deriving valuable insights from data.

ETL Tools 52

ETL Tools Database-centric Data Mining Data Cleanse 52

Precisely

MARCH 9, 2023

As cloud computing platforms make it possible to perform advanced analytics on ever larger and more diverse data sets, new and innovative approaches have emerged for storing, preprocessing, and analyzing information. A data warehouse implies a certain degree of preprocessing, or at the very least, an organized and well-defined data model.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

DataKitchen

FEBRUARY 27, 2024

Just as pilots rely on auto-pilot technologies because they understand how they work and trust the data fed into them, data engineers and business leaders must foster a similar level of trust in LLMs. This trust hinges on the quality of the input data and the transparency of the Data Journey.

Data Engineering 48

Data Engineering Data Engineer Engineering Unstructured Data 48

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 Unstructured Data Data Architecture Government 108

Knowledge Hut

MAY 31, 2023

Artificial intelligence (AI) projects are software-based initiatives that utilize machine learning, deep learning, natural language processing, computer vision, and other AI technologies to develop intelligent programs capable of performing various tasks with minimal human intervention.

Project 96

Project Healthcare Deep Learning Transportation 96

Cloudera

OCTOBER 28, 2021

In reality, we are way ahead in the use of data (possibly hundreds of years ahead!), but behind in our use of tools and technology to manage the data optimally to get the most value out of it. In the last few years, Commercial Insurers have been making great strides in expanding the use of their data.

Insurance 95

Insurance Transportation Unstructured Data Manufacturing 95

Knowledge Hut

DECEMBER 26, 2023

Thus, to build a career in Data Science, you need to be familiar with how the business operates, its business model, strategies, problems, and challenges. Data Science Roles As Data Science is a broad field, you will find multiple different roles with different responsibilities.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

AltexSoft

OCTOBER 25, 2021

Its deep learning natural language processing algorithm is best in class for alleviating clinical documentation burnout, which is one of the main problems of healthcare technology. This allows machines to extract value even from unstructured data. Healthcare organizations generate a lot of text data. Source: Linguamatics.

Medical 52

Medical Healthcare Process Hospitality 52

Data Engineering Weekly

JUNE 4, 2023

[link] LlamaIndex: Combining Text-to-SQL with Semantic Search for Retrieval Augmented Generation A query engine can leverage the expressivity of SQL over structured data and join it with unstructured context from a vector database - The future of data processing. The author writes a comprehensive guide about PET.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 52

ProjectPro

FEBRUARY 16, 2023

Business Intelligence and Artificial Intelligence are popular technologies that help organizations turn raw data into actionable insights. While both BI and AI provide data-driven insights, they differ in how they help businesses gain a competitive edge in the data-driven marketplace.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

Knowledge Hut

JULY 28, 2023

We will see how the two technologies differ or overlap and will answer the question - What is the difference between machine learning and deep learning? Data Types and Dimensionality ML algorithms work well with structured and tabular data, where the number of features is relatively small. When to Use Deep Learning 1.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 52

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Monte Carlo

AUGUST 31, 2023

Data is a priority for your CEO, as it often is for digital-first companies, and she is fluent in the latest and greatest business intelligence tools. Your CTO is excited about migrating to the cloud, and constantly sends your team articles highlighting performance measurements against some of the latest technologies.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

Cloudera

DECEMBER 11, 2020

Based in Germany, Merck KGaA is one of the leading science and technology companies, operating across healthcare, life science, and performance materials business areas. From advancing gene-editing technologies and discovering unique ways to treat the most challenging diseases, to enabling the intelligence of devices.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Knowledge Hut

NOVEMBER 28, 2023

The data goes through various stages, such as cleansing, processing, warehousing, and some other processes, before the data scientists start analyzing the data they have garnered. The data analysis stage is important as the data scientists extract value and knowledge from the processed, structured data.

Data Science 52

Data Science Telecommunication Recruitment Finance 52

Data Engineering Podcast

JUNE 17, 2021

Summary Working with unstructured data has typically been a motivation for a data lake. Kirk Marple has spent years working with data systems and the media industry, which inspired him to build a platform for automatically organizing your unstructured assets to make them more valuable.

Unstructured Data 100

Unstructured Data Data Warehouse Metadata Media 100

Ascend.io

NOVEMBER 21, 2023

Extract The initial stage of the ELT process is the extraction of data from various source systems. This phase involves collecting raw data from the sources, which can range from structured data in SQL or NoSQL servers, CRM and ERP systems, to unstructured data from text files, emails, and web pages.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Knowledge Hut

JULY 26, 2023

These datasets typically involve high volume, velocity, variety, and veracity, which are often referred to as the 4 v's of Big Data: Volume: Volume refers to the vast amount of data generated and collected from various sources. Managing and analyzing such large volumes of data requires specialized tools and technologies.

Big Data 52

Big Data Data Cleanse Retail Healthcare 52

Knowledge Hut

DECEMBER 29, 2023

The market for analytics is flourishing, as is the usage of the phrase Data Science. Professionals from a variety of disciplines use data in their day-to-day operations and feel the need to understand cutting-edge technology to get maximum insights from the data, therefore contributing to the growth of the organization.

Data Science 98

Data Science Data Mining Deep Learning Programming Language 98

Knowledge Hut

JANUARY 19, 2024

With businesses relying heavily on data, the demand for skilled data scientists has skyrocketed. In data science, we use various tools, processes, and algorithms to extract insights from structured and unstructured data. Data Structures Data structures are the architects of data manipulation.

Data Science 52

Data Science Machine Learning Datasets Algorithm 52

Knowledge Hut

MAY 31, 2023

Companies utilize different approaches to deal with data in order to extract information from structured, semi-structured, or unstructured data sets. Business Intelligence is one such approach that helps professionals to extract valuable information from structured data.

Business Intelligence 52

Business Intelligence BI Business Analyst Consulting 52

Rockset

JULY 29, 2022

This fast, serverless, highly scalable, and cost-effective multi-cloud data warehouse has built-in machine learning, business intelligence, and geospatial analysis capabilities for querying massive amounts of structured and semi-structured data. So, it’s not real-time data. Pricing starts at $0.25

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 52

ProjectPro

DECEMBER 7, 2021

In broader terms, two types of data -- structured and unstructured data -- flow through a data pipeline. The structured data comprises data that can be saved and retrieved in a fixed format, like email addresses, locations, or phone numbers. Step 1- Automating the Lakehouse's data intake.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Knowledge Hut

JUNE 19, 2023

Businesses use various data visualization techniques to present information from structured, semi-structured, or unstructured data collections. Adapting to business intelligence skills is necessary to survive in the rapidly growing technology industry.

Business Intelligence 52

Business Intelligence BI Programming Language Recruitment 52

ProjectPro

JULY 22, 2016

The powerful data lake architecture leverages analytics capabilities for big data processing and helps businesses address operational challenges which were difficult to be solved using conventional data warehousing technologies. Table of Contents Data Lake- A perfect place for Unstructured Data What is a Data Lake?

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40

ProjectPro

SEPTEMBER 30, 2014

To understand the significance of big data and Hadoop for ETL professionals read this article to endorse the awareness on why is this the best time to pursue a career in big data Hadoop for all data warehousing and ETL professionals. As things stand currently, both the technologies are here to stay in the near future.

Hadoop 52

Hadoop Unstructured Data ETL Tools ETL System 52

Zalando Engineering

NOVEMBER 6, 2017

Ana was always asking questions: What ways can data science add value to Zalando? How can data be leveraged in new ways? How can sense be made out of all the data being generated in the fashion ecosystem online? What new technologies should we be investigating ? Quality structured data is not easy to get in fashion.

Data Science 40

Data Science Deep Learning Media Unstructured Data 40

ProjectPro

OCTOBER 15, 2014

Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Hadoop technology is the buzz word these days but most of the IT professionals still are not aware of the key components that comprise the Hadoop Ecosystem. Pig supports Avro file format.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Ascend.io

AUGUST 31, 2023

For example, unlike traditional platforms with set schemas, data lakes adapt to frequently changing data structures at points where the data is loaded , accessed, and used. Harnessing the Power of Data Pipelines The EtLT approach stands out as the standard and prevailing demand in today’s data space.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

ProjectPro

JUNE 6, 2015

How can business intelligence scale and analyse the growing data heap? Business Intelligence (BI) combines human knowledge, technologies like distributed computing, and Artificial Intelligence, and big data analytics to augment business decisions for driving enterprise’s success. In BI we just consider structured data.

Business Intelligence 40

Business Intelligence Big Data BI Hadoop 40