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. Why Use MongoDB for Data Science?

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

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. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

APRIL 24, 2023

Data lakes are useful, flexible data storage repositories that enable many types of data to be stored in its rawest state. Notice how Snowflake dutifully avoids (what may be a false) dichotomy by simply calling themselves a “data cloud.” AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

Knowledge Hut

DECEMBER 26, 2023

According to the World Economic Forum, the amount of data generated per day will reach 463 exabytes (1 exabyte = 10 9 gigabytes) globally by the year 2025. Thus, almost every organization has access to large volumes of rich data and needs “experts” who can generate insights from this rich data.

Data Science 97

Data Science BI Business Intelligence Data Mining 97

ProjectPro

SEPTEMBER 9, 2021

Apache Hive Architecture Apache Hive has a simple architecture with a Hive interface, and it uses HDFS for data storage. Data in Apache Hive can come from multiple servers and sources for effective and efficient processing in a distributed manner. Spark SQL, for instance, enables structured data processing with SQL.

Hadoop 52

Hadoop Big Data Tools Java SQL 52

Ascend.io

NOVEMBER 21, 2023

The emergence of cloud data warehouses, offering scalable and cost-effective data storage and processing capabilities, initiated a pivotal shift in data management methodologies. Extract The initial stage of the ELT process is the extraction of data from various source systems.

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

Monte Carlo

AUGUST 31, 2023

Your downstream data consumers including product analysts, marketing leaders, and sales teams rely on data-driven tools like CRMs, CXPs, CMSs, and any other acronym under the sun to do their jobs quickly and effectively. But what happens when the data is wrong?

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 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

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

Rockset

JULY 29, 2022

This consistency promotes data integrity, so you can trust the insights to make informed decisions. Additionally, data warehouses are great at offering historical intelligence. However, organizations today are moving beyond just batch analytics on historical data. So, it’s not real-time data. Pricing starts at $0.25

Data Analytics 52

Data Analytics Data Warehouse Datasets Google Cloud 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

ProjectPro

SEPTEMBER 1, 2015

Once big data is loaded into Hadoop, what is the best way to use this data? Collecting huge amounts of unstructured data does not help unless there is an effective way to draw meaningful insights from it. Hadoop Developers have to filter and aggregate the data to leverage it for business analytics.

Hadoop 40

Hadoop Java Unstructured Data SQL 40

Monte Carlo

AUGUST 25, 2023

That’s why it’s essential for teams to choose the right architecture for the storage layer of their data stack. But, the options for data storage are evolving quickly. So let’s get to the bottom of the big question: what kind of data storage layer will provide the strongest foundation for your data platform?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

ProjectPro

NOVEMBER 14, 2015

Big data has taken over many aspects of our lives and as it continues to grow and expand, big data is creating the need for better and faster data storage and analysis. These Apache Hadoop projects are mostly into migration, integration, scalability, data analytics, and streaming analysis.

Hadoop 52

Hadoop Project Big Data Healthcare 52

Knowledge Hut

SEPTEMBER 26, 2023

Organizations can harness the power of the cloud, easily scaling resources up or down to meet their evolving data processing demands. Supports Structured and Unstructured Data: One of Azure Synapse's standout features is its versatility in handling a wide array of data types.

Data Lake 52

Data Lake Database-centric Pipeline-centric Machine Learning 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

It can store any type of data — structured, unstructured, and semi-structured — in its native format, providing a highly scalable and adaptable solution for diverse data needs. Data is stored in a schema-on-write approach, which means data is cleaned, transformed, and structured before storing.

Data Management 52

Data Management Data Lake Management Data Governance 52

AltexSoft

JUNE 26, 2023

Commonly, the entire flow is fully automated and consists of three main steps — data extraction, transformation, and loading ( ETL or ELT , for short, depending on the order of the operations.) Dive deeper into the subject by reading our article Data Integration: Approaches, Techniques, Tools, and Best Practices for Implementation.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JULY 24, 2023

NoSQL Databases NoSQL databases are non-relational databases (that do not store data in rows or columns) more effective than conventional relational databases (databases that store information in a tabular format) in handling unstructured and semi-structured data.

Database 52

Database NoSQL Management Relational Database 52

ProjectPro

JANUARY 19, 2022

Azure Data Engineer Job Description | Accenture Azure Certified Data Engineer Azure Data Engineer Certification Microsoft Azure Projects for Practice to Enhance Your Portfolio FAQs Who is an Azure Data Engineer? This is where the Azure Data Engineer enters the picture. Who should take the certification exam?

Data Engineering 52

Data Engineering Data Engineer Engineering Scala 52

Knowledge Hut

MARCH 27, 2024

Let's check some of the best big data analytics tools and free big data analytics tools. 14 Most Popular Big Data Analytics Tools Open-source big data analytics tools are intended to be publicly accessible and are typically managed and maintained by organizations with a specific mission. are accessible via URL.

Big Data 52

Big Data Data Analytics MongoDB Big Data Tools 52

Monte Carlo

JUNE 14, 2023

This frequently involves, in some order, extraction (from a source system), transformation (where data is combined with other data and put into the desired format), and loading (into storage where it can be accessed). Most organizations deploy some or all of these data pipeline architectures.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Knowledge Hut

NOVEMBER 17, 2023

Today, data is everything, and every technology runs around managing, storing, accessing, and processing this data. After the introduction of cloud computing, the need for managing expanding data is getting more critical. Below are the benefits of why data scientists across the globe highly adopt AWS.

AWS 52

AWS Data Science Certification Amazon Web Services 52

Edureka

FEBRUARY 9, 2023

Azure Data Engineers Jobs – The Demand Azure Data Engineer Skills What does an Azure Data Engineer Do? Who is an Azure Data Engineer? Data is an organization’s most valuable asset, so making sure it can be accessed quickly and securely should be a top priority.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Mining 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

Edureka

AUGUST 2, 2023

Data processing analysts are experts in data who have a special combination of technical abilities and subject-matter expertise. They are essential to the data lifecycle because they take unstructured data and turn it into something that can be used.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

Knowledge Hut

DECEMBER 26, 2023

The spectrum of sources from which data is collected for the study in Data Science is broad. These data have been accessible to us because of the advanced and latest technologies which are used in the collection of data. NoSQL is a distributed data storage that is becoming increasingly popular.

Data Engineering 98

Data Engineering Data Engineer Engineering Pipeline-centric 98

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

Monte Carlo

JANUARY 25, 2023

In this article, we’ll take a closer look at the data storage level of the data stack to determine when to invest in storage and compute tooling, what “build versus buy” really means when it comes to storage and compute, and how our five considerations might impact your decision. Let’s jump in!

Data Warehouse 40

Data Warehouse Building Data Lake Data Storage 40

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 AWS Relational Database 52

Snowflake

MARCH 30, 2023

Snowflake can also ingest external tables from on-premise s data sources via S3-compliant data storage APIs. Batch/file-based data is modeled into the raw vault table structures as the hub, link, and satellite tables illustrated at the beginning of this post. Enter Snowpark !

Engineering 82

Engineering Raw Data Data Science Scala 82

AltexSoft

AUGUST 4, 2021

Some sweets are presented on your display cases for quick access while the rest is kept in the storeroom. Now let’s think of sweets as the data required for your company’s daily operations. Initially, DWs dealt with structured data presented in tabular forms. Data mart designing.

Data Lake 64

Data Lake Data Warehouse ETL Tools Telecommunication 64

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

AltexSoft

SEPTEMBER 23, 2021

It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. With a data hub, businesses receive the means to structure, and harmonize information collected from various sources. Data lake vs data hub. Azure Data Factory.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Edureka

FEBRUARY 7, 2023

In this case, the service provider creates a managed service that allows users to access these services on demand. For data access, Synapse SQL, an enhanced version of TSQL, is used. Storage for Azure VMs is provided by Azure Disks (Virtual Machines). 13) Examine the capabilities of Azure storage explorer.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52