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

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

Precisely

SEPTEMBER 6, 2023

.” Poor data quality impedes the success of data programs, hampers data integration efforts, limits data integrity causing big data governance challenges. To truly succeed in an increasingly data-driven world, organizations need data governance. The results are clear.

Data Governance 52

Data Governance Big Data Government Unstructured Data 52

Knowledge Hut

DECEMBER 26, 2023

In recent years, with the advent of technology, data has been considered to be a valuable asset in both large-scale and small-scale organizations. Data as a resource requires skilled professionals to be collected, interpreted, and stored safely. Data Management Data management is an integral part of high-scale organizations.

Data Science 52

Data Science Scala Programming Language R (Programming) 52

AltexSoft

MARCH 2, 2023

As the amount of enterprise data continues to surge, businesses are increasingly recognizing the importance of data governance — the framework for managing an organization’s data assets for accuracy, consistency, security, and effective use. What is data governance? billion in 2020 to $5.28

Data Governance 52

Data Governance Government Healthcare Programming 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

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

The Modern Data Company

MAY 8, 2023

Data lakes, data warehouses, data hubs, data lakehouses, and data operating systems are data management and storage solutions designed to meet different needs in data analytics, integration, and processing. Potential downsides of data lakes include governance and integration challenges.

Data Management 52

Data Management Data Lake Management Data Governance 52

Cloudera

MAY 14, 2024

Hybrid cloud plays a central role in many of today’s emerging innovations—most notably artificial intelligence (AI) and other emerging technologies that create new business value and improve operational efficiencies. But getting there requires data, and a lot of it. What do we mean by ‘true’ hybrid? Let’s dive deeper.

Cloud 85

Cloud Data Governance Unstructured Data Data Architecture 85

Knowledge Hut

APRIL 25, 2024

It refers to gathering and processing sizable amounts of data to produce insights that may be used by an organization to improve its various facets. Due to this, businesses from a variety of industries are concentrating on implementing this technology. The only component of this huge data analytics is data analytics.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

AltexSoft

JUNE 26, 2023

Read our article on Hotel Data Management to have a full picture of what information can be collected to boost revenue and customer satisfaction in hospitality. While all three are about data acquisition, they have distinct differences. Data integration , on the other hand, happens later in the data management flow.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

Knowledge Hut

JULY 24, 2023

Get ready to discover fascinating insights, uncover mind-boggling facts, and explore the transformative potential of cutting-edge technologies like blockchain, cloud computing, and artificial intelligence. To kick-start your career in database management, you can take the best database courses.

Database 52

Database NoSQL Management Relational Database 52

Ascend.io

JULY 19, 2023

In this article, we provide practical, actionable steps to kick-start your data mesh implementation using the well-established approach of managing People, Processes, and Technology. Consider this your primer to stop overthinking, start acting, and truly harness the power of data mesh.

Data Governance 40

Data Governance Government Metadata Data 40

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

DareData

JANUARY 30, 2023

At a critical part of a data ingestion process is the data pipeline , a series of steps that are used to gather, transform, and store data. They can be simple or complex, and they can involve multiple steps, technologies or formats such as CSV, Tabular or JSON formats.

Data Engineering 52

Data Engineering Data Engineer NoSQL Engineering 52

Snowflake

MARCH 30, 2023

3EJHjvm Once a business need is defined and a minimal viable product ( MVP ) is scoped, the data management phase begins with: Data ingestion: Data is acquired, cleansed, and curated before it is transformed. Feature engineering: Data is transformed to support ML model training. ML workflow, ubr.to/3EJHjvm

Engineering 82

Engineering Raw Data Data Science Scala 82

ProjectPro

JANUARY 27, 2023

If you're wondering how the ETL process can drive your company to a new era of success, this blog will help you discover what use cases of ETL make it a critical component in many data management and analytic systems. However, the vast volume of data will overwhelm you if you start looking at historical trends.

BI 52

BI ETL Tools Retail Healthcare 52

Monte Carlo

APRIL 1, 2021

Over the past few years, data lakes have emerged as a must-have for the modern data stack. But while the technologies powering our access and analysis of data have matured, the mechanics behind understanding this data in a distributed environment have lagged behind. Data discovery tools and platforms can help.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Knowledge Hut

SEPTEMBER 26, 2023

The demand for data professionals with business intelligence skills has increased significantly in recent years. With technological advancements and digital transformations, businesses are taking data very seriously. In today's business environment, data is an invaluable asset. The certification cost is $165 USD.

BI 52

BI Business Intelligence Raw Data Data Analysis 52

AltexSoft

AUGUST 22, 2022

Some would say that it’s not a big deal, however, these mixed environments have resulted in the complexities of managing disjointed data and business processes. With these challenges in enterprise data management, there has to be an approach to overcoming them, right? The solution is called a data fabric.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

AltexSoft

NOVEMBER 10, 2021

Well, there’s a new phenomenon in data management that received the name of a data lakehouse. The pun being obvious, there’s more to that than just a new term: Data lakehouses combine the best features of both data lakes and data warehouses and this post will explain this all. Data warehouse.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

SEPTEMBER 23, 2021

We’ll also analyze some of the data hub products existing in the market to explore how this technology works and what it actually can do. What is Data Hub? A data hub is a central mediation point between various data sources and data consumers. A data hub serves as a gateway to dispense the required data.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

JULY 29, 2022

The biggest star of the Big Data world, Hadoop was named after a yellow stuffed elephant that belonged to the 2-year son of computer scientist Doug Cutting. The toy became the official logo of the technology, used by the major Internet players — such as Twitter, LinkedIn, eBay, and Amazon. How data engineering works under the hood.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

Cloudera

OCTOBER 30, 2018

The abundant growth of data, maturation of machine algorithms, and future regulatory compliance demands from the European Union’s General Data Protection Regulation (GDPR) will shift the landscape for creating a single source of the truth for customer data. Additionally, they only provide one piece of the puzzle.

Unstructured Data 42

Unstructured Data Data Lake Algorithm Machine Learning 42

AltexSoft

OCTOBER 8, 2021

The bad news is, integrating data can become a tedious task, especially when done manually. Luckily, there are various data integration tools that support automation and provide a unified data view for more efficient data management. Data integration process. IBM DataStage Designer interface. Source: G2.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

ProjectPro

JANUARY 31, 2022

Extensive Network of Partners Data scientists leverage various tools, and the machine learning (ML) sector is continually expanding, with the release of new data science tools every year. By doing so, Snowflake has overcome one of the most significant constraints associated with traditional database technology.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 15, 2021

With SQL, machine learning, real-time data streaming, graph processing, and other features, this leads to incredibly rapid big data processing. DataFrames are used by Spark SQL to accommodate structured and semi-structured data. Trino is a distributed query tool for effectively querying large volumes of data.

Big Data 52

Big Data Project Metadata Programming Language 52

AltexSoft

MAY 12, 2023

What is unstructured data? Definition and examples Unstructured data , in its simplest form, refers to any data that does not have a pre-defined structure or organization. It can come in different forms, such as text documents, emails, images, videos, social media posts, sensor data, etc.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Precisely

JANUARY 23, 2024

Enterprise Challenges in 2024 and Beyond The big-picture process of building data that is accurate, consistent and contextual – or data integrity – calls for a systematic approach combining technology tools, internal change management, and a company-wide commitment to results.

Technology 69

Technology Data Governance Government Data Integration 69

Cloudera

OCTOBER 7, 2021

Within the context of a data mesh architecture, I will present industry settings / use cases where the particular architecture is relevant and highlight the business value that it delivers against business and technology areas. need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g.,

Architecture 122

Architecture Metadata Government Kafka 122

phData: Data Engineering

JULY 18, 2023

Yet, those that do achieve this level of maturity from their data stack are able to unlock breakthrough successes while leaving competitors years behind in innovation. Perhaps the largest roadblock of this data-driven utopia is the continued reliance on a patchwork of legacy, on-premise technologies like Teradata, Netezza, Oracle, etc.,

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

AltexSoft

MARCH 14, 2023

This development has paved the way for a suite of cloud-native data tools that are user-friendly, scalable, and affordable. Known as the Modern Data Stack (MDS) , this suite of tools and technologies has transformed how businesses approach data management and analysis. Data storage component in a modern data stack.

IT 59

IT Data Warehouse Data Governance Data Lake 59

AltexSoft

MARCH 30, 2023

The answer is simple: They use the same technology to make the most of data. Along with thousands of other data-driven organizations from different industries, the above-mentioned leaders opted for Databrick to guide strategic business decisions. Besides that, it’s fully compatible with various data ingestion and ETL tools.

Scala 64

Scala Data Lake BI Google Cloud 64

U-Next

SEPTEMBER 29, 2022

There is no guarantee that a company has a data-driven culture or is data-driven merely because it collects a great deal of data. In order to make informed decisions, organizations need to leverage data. . Types of Data in an Organization . A structured data record consists of a very fixed field of data.

Management 52

Management Unstructured Data Data Government 52