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

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

We will also address some of the key distinctions between platforms like Hadoop and Snowflake, which have emerged as valuable tools in the quest to process and analyze ever larger volumes of structured, semi-structured, and unstructured data.

Data Lake 59

Data Lake Data Warehouse Hadoop Raw Data 59

Propel Data

OCTOBER 11, 2022

The main difference between data lakes and data warehouses is data lakes allow unstructured data, but data warehouses need structured data.

Data Lake 40

Data Lake Data Warehouse Unstructured Data Data Analytics 40

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. 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.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 52

The Modern Data Company

MAY 10, 2023

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? 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

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? 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

To choose the most suitable data management solution for your organization, consider the following factors: Data types and formats: Do you primarily work with structured, unstructured, or semi-structured data? Consider whether you need a solution that supports one or multiple data formats.

Data Management 52

Data Management Management Data Lake Data Warehouse 52

U-Next

MARCH 1, 2023

What is a data lake, and how does it differ from a data warehouse? Data lakes contain raw, unstructured data of an organization, which can be stored indefinitely – either immediately or in the future. What is AWS Kinesis?

Data Engineering 75

Data Engineering Data Engineer Non-relational Database Engineering 75

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 111

IT Unstructured Data Data Architecture Government 111

DataKitchen

FEBRUARY 27, 2024

Challenges in Developing Reliable LLMs Organizations venturing into LLM development encounter several hurdles: Data Location: Critical data often resides in spreadsheets, characterized by a blend of text, logic, and mathematics.

Data Engineering 48

Data Engineering Data Engineer Engineering Unstructured Data 48

AltexSoft

OCTOBER 25, 2021

This allows machines to extract value even from unstructured data. Healthcare organizations generate a lot of text data. Some of it is structured , or organized into specific fields of an EHR. Unstructured data is unavoidable, yet extremely valuable. The many healthcare factors hidden in unstructured data.

Medical 52

Medical Healthcare Process Hospitality 52

AltexSoft

AUGUST 29, 2023

Data sources can be broadly classified into three categories. Structured data sources. These are the most organized forms of data, often originating from relational databases and tables where the structure is clearly defined. Semi-structured data sources. Unstructured data sources.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Knowledge Hut

JULY 28, 2023

Data Types and Dimensionality ML algorithms work well with structured and tabular data, where the number of features is relatively small. DL models excel at handling unstructured data such as images, audio, and text, where the data has a large number of features or high dimensionality.

Deep Learning 52

Deep Learning Machine Learning Unstructured Data Algorithm 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. Text data served up via Solr’s powerful analytics engine and APIs.

Unstructured Data 81

Unstructured Data Pharmaceutical Data Warehouse MySQL 81

Cloudera

OCTOBER 28, 2021

In the last few years, Commercial Insurers have been making great strides in expanding the use of their data. The approach is very evolutionary; the initial focus tends to be aimed at cost savings and starts with structured data. Then there is a recognition that there is so much more that can be done with the data.

Insurance 97

Insurance Transportation Unstructured Data Manufacturing 97

Knowledge Hut

MAY 31, 2023

Resume Parser Language: Python Data set: text file Source code: keras-english-resume-parser-and-analyzer An AI-powered tool called a resume parser pulls pertinent data from resumes or CVs and turns it into structured data.

Project 96

Project Healthcare Transportation Deep Learning 96

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.

Data Engineering 52

Data Engineering Data Engineer Engineering Medical 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

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data.

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Grouparoo

JANUARY 11, 2022

Difference Between Data Warehouse and Data Lake When looking at the difference between data lake and data warehouse, the following key properties distinguish data lakes vs data warehouses. In addition, data warehouses require more complex processing and management applications that also increase costs.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Cloudera

DECEMBER 11, 2020

It established a data governance framework within its enterprise data lake. Powered and supported by Cloudera, this framework brings together disparate data sources, combining internal data with public data, and structured data with unstructured data.

Data Lake 98

Data Lake Government Data Security Unstructured Data 98

Knowledge Hut

DECEMBER 26, 2023

The responsibilities of Data Analysts are to acquire massive amounts of data, visualize, transform, manage and process the data, and prepare data for business communications. The primary responsibility of a Data Scientist is to provide actionable business insights based on their analysis of the data.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

ProjectPro

FEBRUARY 16, 2023

Focus Historical data analysis, reporting, and visualization. Input Data Structured data from various sources, such as databases, spreadsheets, and ERP systems. Structured, semi-structured, and unstructured data from multiple sources, such as social media, IoT devices, and sensors.

Business Intelligence 52

Business Intelligence BI Data Mining Raw Data 52

Monte Carlo

AUGUST 31, 2023

We’ll take a closer look at variables that can impact your data next. Migration to the cloud Twenty years ago, your data warehouse (a place to transform and store structured data) probably would have lived in an office basement, not on AWS or Azure. Rise of the Data Lakehouse Data warehouse or data lake?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52

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

Monte Carlo

APRIL 24, 2023

AWS is one of the most popular data lake vendors. AWS Lake Formation offers an alternative for data teams looking for a more structured data lake or data lakehouse solution. A picture of their Lake Formation architecture. Not to mention seamless integration with the Oracle ecosystem.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Data Visualization Graphic representation of a set or sets of data. Database A collection of structured data.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

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

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

SEPTEMBER 9, 2021

Spark SQL, for instance, enables structured data processing with SQL. Hive , for instance, does not support sub-queries and unstructured data. Data update and deletion operations are also not possible with Hive. Apache Spark also offers hassle-free integration with other high-level tools.

Hadoop 52

Hadoop Big Data Tools Java SQL 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 AWS Kafka 52

Knowledge Hut

JUNE 16, 2023

Data preparation: Because of flaws, redundancy, missing numbers, and other issues, data gathered from numerous sources is always in a raw format. After the data has been extracted, data analysts must transform the unstructured data into structured data by fixing data errors, removing unnecessary data, and identifying potential data.

Programming Language 52

Programming Language Data Preparation Cloud Computing Data Science 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.

Cloud 72

Cloud Data Lake Cloud Storage Metadata 72

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

ProjectPro

OCTOBER 15, 2014

Generally data to be stored in the database is categorized into 3 types namely Structured Data, Semi Structured Data and Unstructured Data. We generally refer to Unstructured Data as “Big Data” and the framework that is used for processing Big Data is popularly known as Hadoop.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

ProjectPro

JULY 22, 2016

Data warehouses do a good job for what they are meant to do, but with disparate data sources and different data types like transaction logs, social media data, tweets, user reviews, and clickstream data –Data Lakes fulfil a critical need. Data Warehouses do not retain all data whereas Data Lakes do.

Data Lake 40

Data Lake Data Warehouse Hadoop Unstructured Data 40