ProjectPro

FEBRUARY 16, 2023

With so much riding on the efficiency of ETL processes for data engineering teams, it is essential to take a deep dive into the complex world of ETL on AWS to take your data management to the next level. Data integration with ETL has changed in the last three decades.

AWS 52

AWS Data Management ETL Tools Management 52

AltexSoft

SEPTEMBER 10, 2021

To get a single unified view of all information, companies opt for data integration. In this article, you will learn what data integration is in general, key approaches and strategies to integrate siloed data, tools to consider, and more. What is data integration and why is it important?

Data Integration 52

Data Integration Data Consolidation Data Warehouse BI 52

Precisely

SEPTEMBER 9, 2024

“Enterprises are more mature in managing the quality of structured data than newer data types.” Organizations are adept at managing the quality of structured data, but management of unstructured and semi-structured data is less mature. • Adopt process automation platforms.

Management 64

Management High Quality Data Structured Data Data Lake 64

Data Engineering Weekly

MAY 5, 2024

link] LinkedIn: LakeChime - A Data Trigger Service for Modern Data Lakes LinkedIn points out two critical flaws in a partitioned approach to data management. The granularity of partition creation constrained data consumption. However, the Map and Array comes with its cost.

Data Engineer 67

Data Engineer Data Engineering Engineering Google Cloud 67

Knowledge Hut

MARCH 15, 2024

Whether you like the flexible landscape of NoSQL or the ordered accuracy of RDBMS, knowing these distinctions is essential for developing successful data management strategies. RDBMS vs NoSQL: Features Here's a brief overview of the features of both RDBMS and NoSQL, pointwise: RDBMS: Utilizes structured tables to organize data.

NoSQL 52

NoSQL Database-centric Relational Database PostgreSQL 52

ThoughtSpot

MARCH 5, 2024

While AI-powered, self-service BI platforms like ThoughtSpot can fully operationalize insights at scale by delivering visual data exploration and discovery, it still requires robust underlying data management. Snowflake's new dynamic tables feature redefines how BI and analytics teams approach data transformation pipelines.

BI 111

BI Datasets Raw Data SQL 111

Monte Carlo

OCTOBER 10, 2024

Table of Contents What Does an AI Data Quality Analyst Do? The role is usually on a Data Governance, Analytics Engineering, Data Engineering, or Data Science team, depending on how the data organization is structured. Data Cleaning and Preprocessing : Techniques to identify and remove errors.

Unstructured Data 52

Unstructured Data Google Cloud Machine Learning 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 Raw Data 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. What Is ELT? So, what exactly is ELT?

Raw Data 52

Raw Data Data Warehouse Data Cleanse Data Integration 52

RandomTrees

SEPTEMBER 17, 2024

In the realm of big data and AI, managing and securing data assets efficiently is crucial. Databricks addresses this challenge with Unity Catalog, a comprehensive governance solution designed to streamline and secure data management across Databricks workspaces. Advantages of the Unity Catalog 1.

Data Governance 52

Data Governance Government Metadata Machine Learning 52

Striim

SEPTEMBER 11, 2024

In an ETL-based architecture, data is first extracted from source systems, then transformed into a structured format, and finally loaded into data stores, typically data warehouses. This method is advantageous when dealing with structured data that requires pre-processing before storage.

Data Pipeline 98

Data Pipeline Designing Data Lake Data Warehouse 98

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

Precisely

SEPTEMBER 6, 2023

However, fewer than half of survey respondents rate their trust in data as “high” or “very high.” ” Poor data quality impedes the success of data programs, hampers data integration efforts, limits data integrity causing big data governance challenges.

Data Governance 52

Data Governance Big Data Government Unstructured Data 52

Knowledge Hut

APRIL 25, 2024

Data management The process of obtaining, storing, and using data in a cost-effective, effective, and secure way is known as data management. As businesses increasingly rely on intangible assets to create value, an efficient data management strategy is more important than ever.

Big Data 52

Big Data Data Analytics Manufacturing Retail 52

Knowledge Hut

APRIL 23, 2024

Big Data vs Small Data: Function Variety Big Data encompasses diverse data types, including structured, unstructured, and semi-structured data. It involves handling data from various sources such as text documents, images, videos, social media posts, and more.

Big Data 52

Big Data Datasets Data Analysis Media 52

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

Ascend.io

FEBRUARY 28, 2024

Read More: AI Data Platform: Key Requirements for Fueling AI Initiatives How Data Engineering Enables AI Data engineering is the backbone of AI’s potential to transform industries , offering the essential infrastructure that powers AI algorithms.

Data Engineer 52

Data Engineer Data Engineering Engineering Metadata 52

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making. Better together.

Unstructured Data 74

Unstructured Data Data Lake Data Architecture Data 74

Knowledge Hut

MARCH 27, 2024

Primarily used for organizing and optimizing data to perform specific operations within a program efficiently. Relationships Allows the establishment of relationships between different tables, supporting data integrity and normalization. Supports complex query relationships and ensures data integrity.

Database 52

Database Relational Database Algorithm PostgreSQL 52

Striim

MAY 1, 2024

The sheer volume of data generated from the increasing package deliveries overwhelmed existing data management systems, underscoring a critical need for more advanced data handling capabilities. The absence of real-time data processing capabilities hindered UPS Capital’s risk management and rapid response efforts.

Google Cloud 52

Google Cloud Insurance Finance Machine Learning 52

Edureka

AUGUST 2, 2023

Their efforts make ensuring that data is accurate, dependable, and consistent, laying the groundwork for data analysis and decision-making. What does a Data Processing Analysts do ? A data processing analyst’s job description includes a variety of duties that are essential to efficient data management.

Data Process 52

Data Process Process Data Cleanse Data Mining 52

DareData

JANUARY 30, 2023

AWS Glue: A fully managed data orchestrator service offered by Amazon Web Services (AWS). Talend Data Fabric: A comprehensive data management platform that includes a range of tools for data integration, data quality, and data governance.

Data Engineer 52

Data Engineer Data Engineering NoSQL Engineering 52

Knowledge Hut

NOVEMBER 3, 2023

The need for efficient and agile data management products is higher than ever before, given the ongoing landscape of data science changes. MongoDB is a NoSQL database that’s been making rounds in the data science community. There are several benefits to MongoDB for data science operations.

MongoDB 52

MongoDB Data Science NoSQL ETL Tools 52

Striim

OCTOBER 11, 2024

Exactly-Once Processing (E1P) Data loss and duplication are critical issues in data pipelines that need to be addressed for reliable data processing. Modern pipelines incorporate Exactly-Once Processing (E1P) to ensure data integrity.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

DataKitchen

FEBRUARY 27, 2024

Feeding this unstructured data into LLMs without proper contextualization risks creating noise instead of clarity. Data Connectivity: Mergers and acquisitions complicate data integration, making it challenging for LLMs to consolidate data across disparate systems.

Data Engineer 47

Data Engineer Data Engineering Engineering Unstructured Data 47

phData: Data Engineering

SEPTEMBER 19, 2023

With many data modeling methodologies and processes available, choosing the right approach can be daunting. This blog will guide you through the best data modeling methodologies and processes for your data lake, helping you make informed decisions and optimize your data management practices. What is a Data Lake?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

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

Edureka

JULY 5, 2024

Users can interactively remove columns, correct data entry errors, and standardize formats, enabling quick issue identification and impact assessment. Data combining and reshaping: Supports operations like join, union, pivot, and split to integrate and structure data sources optimally for analysis in tools like Tableau Desktop.

Data Preparation 40

Data Preparation Process BI ETL Tools 40

AltexSoft

SEPTEMBER 23, 2021

A data hub is a central mediation point between various data sources and data consumers. It’s not a single technology, but rather an architectural approach that unites storages, data integration and orchestration tools. An ETL approach in the DW is considered slow, as it ships data in portions (batches.)

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 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

AltexSoft

MARCH 2, 2023

Data usability ensures that data is available in a structured format that is compatible with traditional business tools and software. Data integrity is about maintaining the quality of data as it is stored, converted, transmitted, and displayed. Learn more about data integrity in our dedicated article.

Data Governance 52

Data Governance Government Programming Healthcare 52

Silectis

JANUARY 3, 2021

Data Architecture Data architecture is a composition of models, rules, and standards for all data systems and interactions between them. Data Catalog An organized inventory of data assets relying on metadata to help with data management. Database A collection of structured data.

Data Engineer 40

Data Engineer Data Engineering Engineering Hadoop 40

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

MAY 14, 2021

A single car connected to the Internet with a telematics device plugged in generates and transmits 25 gigabytes of data hourly at a near-constant velocity. And most of this data has to be handled in real-time or near real-time. Variety is the vector showing the diversity of Big Data. What is Big Data analytics?

Big Data 78

Big Data Data Analytics IT NoSQL 78

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

Towards Data Science

JANUARY 17, 2024

These are key in nearly all data pipelines, allowing for efficient data storage and easier querying and information extraction. They are designed to handle the challenges of big data like size, speed, and structure. Data engineers often face a plethora of choices. Plus, there’s the _delta_log folder.

Big Data 68

Big Data Data Data Storage SQL 68

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