Monte Carlo

AUGUST 25, 2023

Understanding data warehouses A data warehouse is a consolidated storage unit and processing hub for your data. Teams using a data warehouse usually leverage SQL queries for analytics use cases. This same structure aids in maintaining data quality and simplifies how users interact with and understand the data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

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

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. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Cloudera

SEPTEMBER 15, 2022

Today’s platform owners, business owners, data developers, analysts, and engineers create new apps on the Cloudera Data Platform and they must decide where and how to store that data. Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases.

Systems 86

Systems Hadoop Metadata Telecommunication 86

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 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

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

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 80

Unstructured Data Data Warehouse Pharmaceutical MySQL 80

AltexSoft

AUGUST 22, 2022

The self-service functionally allows the entire organization to find relevant data faster and gain valuable insights. Support for different data types and use cases. A data fabric supports structured, unstructured, and semi-structured data whether it comes in real-time or generated in batches.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

SEPTEMBER 23, 2021

A data hub, in turn, is rather a terminal or distribution station: It collects information only to harmonize it, and sends it to the required end-point systems. Data lake vs data hub. A data lake is quite opposite of a DW, as it stores large amounts of both structured and unstructured data.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 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. In our example we use the following External Account.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

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 Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

Monte Carlo

APRIL 1, 2021

Data Catalogs Can Drown in a Data Lake Although exceptionally flexible and scalable, data lakes lack the organization necessary to facilitate proper metadata management and data governance. Data discovery tools and platforms can help. Image courtesy of Adrian on Unsplash.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

ProjectPro

JANUARY 31, 2023

Big data enables businesses to get valuable insights into their products or services. Almost every company employs data models and big data technologies to improve its techniques and marketing campaigns. Most leading companies use big data analytical tools to enhance business decisions and increase revenues.

Big Data 52

Big Data Hadoop Relational Database AWS 52

AltexSoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

JUNE 7, 2021

HDFS master-slave structure. A HDFS Master Node, called a NameNode , keeps metadata with critical information about system files (like their names, locations, number of data blocks in the file, etc.) and keeps track of storage capacity, a volume of data being transferred, etc. Data management and monitoring options.

Big Data Tools 98

Big Data Tools Hadoop Big Data Database-centric 98

Grouparoo

JANUARY 11, 2022

A data warehouse is a unified repository where data from diverse sources undergo aggregation and integration into a usable source of information. To achieve this, a data warehouse will require processes to gather and integrate data, manage data quality, create metadata, and support any regulatory compliance and governance procedures.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Snowflake

MARCH 30, 2023

Automation , because the same loader patterns are used for both and the same metadata tags are expected from both, meaning the applied date timestamp in the business vault will match up with the raw date timestamp where it came from. These methods can be applied to structured and semi-structured data as well.

Engineering 86

Engineering Raw Data Data Science Machine Learning 86

Monte Carlo

JUNE 14, 2023

Amazon S3 – An object storage service for structured and unstructured data, S3 gives you the compute resources to build a data lake from scratch. Data catalog Some organizations choose to implement data catalog solutions for data governance and compliance use cases.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

ProjectPro

AUGUST 11, 2021

This means that a data warehouse is a collection of technologies and components that are used to store data for some strategic use. Data is collected and stored in data warehouses from multiple sources to provide insights into business data. Data from data warehouses is queried using SQL.

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 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.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

ProjectPro

OCTOBER 15, 2014

Hive- Performance Benchmarking Hive vs Pig Pig vs Hive - Differences Pig Hive Procedural Data Flow Language Declarative SQLish Language For Programming For creating reports Mainly used by Researchers and Programmers Mainly used by Data Analysts Operates on the client side of a cluster. Does not have a dedicated metadata database.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

AltexSoft

JULY 29, 2022

How HDFS master-slave structure works. A master node called NameNode maintains metadata with critical information, controls user access to the data blocks, makes decisions on replications, and manages slaves. You can change this parameter manually but the system won’t be able to effectively deal with myriads of tiny data pieces.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Monte Carlo

JANUARY 25, 2023

Image courtesy of Databricks Data warehouse A data warehouse provides data storage and compute for structured data that’s been processed for a defined purpose. Data lake On the other side of the storage and compute coin, a data lake is all about flexibility.

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

Cloudera

SEPTEMBER 6, 2018

It supports a variety of storage engines that can handle raw files, structured data (tables), and unstructured data. It also supports a number of frameworks that can process data in parallel, in batch or in streams, in a variety of languages. Cloudera Enterprise.

Banking 40

Banking Machine Learning Big Data Scala 40

AltexSoft

MAY 12, 2023

In today’s data-driven world, organizations amass vast amounts of information that can unlock significant insights and inform decision-making. A staggering 80 percent of this digital treasure trove is unstructured data, which lacks a pre-defined format or organization. What is unstructured data?

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

ProjectPro

OCTOBER 28, 2015

Hadoop Sqoop and Hadoop Flume are the two tools in Hadoop which is used to gather data from different sources and load them into HDFS. Sqoop in Hadoop is mostly used to extract structured data from databases like Teradata, Oracle, etc., The complexity of the big data system increases with each data source.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52

AltexSoft

NOVEMBER 1, 2023

NER for structuring unstructured data NER plays a pivotal role in converting unstructured text into structured data. Delving into unstructured text data, Watson Natural Language Understanding employs deep learning to decipher underlying meanings and extract metadata.

Deep Learning 52

Deep Learning Machine Learning Datasets Algorithm 52

ProjectPro

AUGUST 24, 2016

Table of Contents Need for HBase HBase –Understanding the Basics HBase Architecture Explained Components of Apache HBase Architecture HMaster Region Server Zookeeper Need for HBase Apache Hadoop has gained popularity in the big data space for storing, managing and processing big data as it can handle high volume of multi-structured data.

Architecture 40

Architecture IT Hadoop NoSQL 40

AltexSoft

JULY 27, 2021

Content-based systems largely depend on the metadata of items. The choice of storage depends on the type of data you’re going to use for recommendations in the first place. Or you may use a mix of different data repositories depending on the purposes. Users get limited to items similar to those they have previously consumed.

Machine Learning 76

Machine Learning Systems Algorithm Deep Learning 76

ProjectPro

OCTOBER 20, 2021

Solutions where speech, text, and other structures, as well as unstructured data, can be used to make better decisions Custom AI The final stage in the AI Journey is when a Custom AI solution to solve business problems can be made. Enterprises in this stage shoot for immediately actionable insights. Discuss a few use cases.

Machine Learning 52

Machine Learning Algorithm Data Science Government 52

ProjectPro

AUGUST 21, 2015

Hadoop vs RDBMS Criteria Hadoop RDBMS Datatypes Processes semi-structured and unstructured data. Processes structured data. Schema Schema on Read Schema on Write Best Fit for Applications Data discovery and Massive Storage/Processing of Unstructured data. are all examples of unstructured data.

Hadoop 40

Hadoop Big Data Metadata Java 40

ProjectPro

DECEMBER 10, 2021

Azure Blob storage is a Microsoft storage offering that is meant explicitly for cloud objects and is suitable for holding vast quantities of unstructured data. Unstructured data, such as text or binary data, does not correspond to a specific data model or description. Explain Azure Blob storage.

BI 52

BI Cloud Computing SQL Database 52

ProjectPro

APRIL 4, 2015

Random Job Distribution Coordinate resource management Self managed resources and worker Process Structured and Semi-Structured Data. Process Unstructured Data. DataNode is the place where the data actually resides before any processing takes place. For e.g. if we have metadata (filename, path, size etc.)

Hadoop 40

Hadoop Big Data Recruitment Java 40

ProjectPro

AUGUST 24, 2021

Thus, as a learner, your goal should be to work on projects that help you explore structured and unstructured data in different formats. Data Warehousing: Data warehousing utilizes and builds a warehouse for storing data. A data engineer interacts with this warehouse almost on an everyday basis.

Data Engineer 52

Data Engineer Data Engineering Coding Project 52

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Cloud 104

Cloud Unstructured Data Metadata Datasets 104