AltexSoft

FEBRUARY 11, 2023

It serves as a foundation for the entire data management strategy and consists of multiple components including data pipelines; , on-premises and cloud storage facilities – data lakes , data warehouses , data hubs ;, data streaming and Big Data analytics solutions ( Hadoop , Spark , Kafka , etc.);

Data Architect 87

Data Architect Certification Generalist Big Data 87

The Modern Data Company

APRIL 15, 2024

The term “Data Product” has become a buzzword, often misused or overstretched. But at its core, a Data Product is much more than just data. This blend ensures that a Data Product is informative, actionable, and adaptable to various needs.

Government 52

Government Metadata Data Data Lake 52

Monte Carlo

NOVEMBER 14, 2023

Databricks announced that Delta tables metadata will also be compatible with the Iceberg format, and Snowflake has also been moving aggressively to integrate with Iceberg. How Apache Iceberg tables structure metadata. Is your data lake a good fit for Iceberg? Limited data type support. Let’s dive in.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

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. Different vendors offering data warehouses, data lakes, and now data lakehouses all offer their own distinct advantages and disadvantages for data teams to consider.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

MAY 14, 2024

At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files. Table formats incorporate aspects like columns, rows, data types, and relationships, but can also include information about the structure of the data itself.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Best Practice 2. Best Practice 3.

Metadata 67

Metadata Relational Database Data Governance Government 67

AltexSoft

OCTOBER 8, 2021

What’s more, that data comes in different forms and its volumes keep growing rapidly every day — hence the name of Big Data. The good news is, businesses can choose the path of data integration to make the most out of the available information. Data integration in a nutshell. Data integration process.

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 52

Databand.ai

JULY 28, 2022

In this very simplified example, we can see an ELT: Some pipeline tasks, probably running by Airflow , are scraping external data sources and collecting data from there. Those tasks are saving the extracted data in the data lake (or warehouse or lakehouse). This technique focuses directly on the data (vs.

Metadata 52

Metadata Data Lake Datasets Data Warehouse 52

Cloudera

MARCH 23, 2022

Figure 1: Apache Iceberg fits the next generation data architecture by abstracting storage layer from analytics layer while introducing net new capabilities like time-travel and partition evolution. #1: Apache Iceberg enables seamless integration between different streaming and processing engines while maintaining data integrity between them.

Metadata 96

Metadata Data Architecture BI Machine Learning 96

AltexSoft

NOVEMBER 10, 2021

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. What is a data lakehouse? Data warehouse vs data lake vs data lakehouse: What’s the difference.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

AUGUST 22, 2022

A data fabric is an architecture design presented as an integration and orchestration layer built on top of multiple disjointed data sources like relational databases , data warehouses , data lakes, data marts , IoT , legacy systems, etc., to provide a unified view of all enterprise data.

Architecture 52

Architecture Metadata Data Lake Machine Learning 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

AltexSoft

NOVEMBER 23, 2021

Not to mention that additional sources are constantly being added through new initiatives like big data analytics , cloud-first, and legacy app modernization. To break data silos and speed up access to all enterprise information, organizations can opt for an advanced data integration technique known as data virtualization.

Process 69

Process Data Lake Metadata Data Warehouse 69

AltexSoft

SEPTEMBER 23, 2021

One of the innovative ways to address this problem is to build a data hub — a platform that unites all your information sources under a single umbrella. This article explains the main concepts of a data hub, its architecture, and how it differs from data warehouses and data lakes. What is Data Hub?

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

AltexSoft

JULY 29, 2022

a runtime environment (sandbox) for classic business intelligence (BI), advanced analysis of large volumes of data, predictive maintenance , and data discovery and exploration; a store for raw data; a tool for large-scale data integration ; and. a suitable technology to implement data lake architecture.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

phData: Data Engineering

SEPTEMBER 27, 2024

Both persistent staging and data lakes involve storing large amounts of raw data. But persistent staging is typically more structured and integrated into your overall customer data pipeline. Building a composable CDP requires some serious data engineering chops. New user sign-up? Workout completed?

Data 52

Data Raw Data Data Lake Architecture 52

ProjectPro

NOVEMBER 15, 2021

Delta Lake Source: Github Delta Lake is an open-source project that allows you to create a Lakehouse design based on data lakes. On top of existing data lakes like S3, ADLS, GCS, and HDFS, Delta Lake enables ACID transactions, scalable metadata handling, and unifies streaming and batch data processing.

Big Data 52

Big Data Project Metadata Programming Language 52

ProjectPro

AUGUST 24, 2021

In this project, you will explore the usage of Databricks Spark on Azure with Spark SQL and build this data pipeline. Upload it to Azure Data lake storage manually. Create a Data Factory pipeline to ingest files. Also, you get a chance to explore Azure Databricks, Data Factory, and Storage services.

Data Engineering 52

Data Engineering Data Engineer Coding Project 52

ProjectPro

JANUARY 31, 2022

It also offers a unique architecture that allows users to quickly build tables and begin querying data without administrative or DBA involvement. Snowflake is a cloud-based data platform that provides excellent manageability regarding data warehousing, data lakes, data analytics, etc. What Does Snowflake Do?

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

ProjectPro

NOVEMBER 30, 2021

Transform Data Once the data is validated, we apply transformations to remove duplicates, perform cleansing, standardization, business rule application, perform data integrity checks, data governance, use aggregations, and many more. Stage Data Data that has been transformed is stored in this layer.

Process 52

Process Data Pipeline Data Warehouse AWS 52

RandomTrees

FEBRUARY 6, 2024

Over the years, the field of data engineering has seen significant changes and paradigm shifts driven by the phenomenal growth of data and by major technological advances such as cloud computing, data lakes, distributed computing, containerization, serverless computing, machine learning, graph database, etc.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

AltexSoft

MAY 12, 2023

Unstructured data , on the other hand, is unpredictable and has no fixed schema, making it more challenging to analyze. Without a fixed schema, the data can vary in structure and organization. There are several widely used unstructured data storage solutions such as data lakes (e.g., Invest in data governance.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. Data and Metadata: Data inputs and data outputs produced based on the application logic.

Architecture 129

Architecture Metadata Kafka Government 129

Precisely

OCTOBER 16, 2023

The cloud is especially well-suited to large-scale storage and big data analytics, due in part to its capacity to handle intensive computing requirements at scale. BI platforms and data warehouses have been replaced by modern data lakes and cloud analytics solutions. Data integrity is also essential.

Cloud 70

Cloud Cloud Computing Metadata Data Governance 70

Edureka

JULY 3, 2024

As data volumes explode across enterprises, the struggle to manage, integrate, and analyze it is getting real. Thankfully, with serverless data integration solutions like Azure Data Factory (ADF), data engineers can easily orchestrate, integrate, transform, and deliver data at scale.

Pipeline-centric 52

Pipeline-centric Data Lake Database-centric Data Pipeline 52

AltexSoft

MARCH 14, 2023

It must collect, analyze, and leverage large amounts of customer data from various sources, including booking history from a CRM system, search queries tracked with Google Analytics, and social media interactions. Built around a cloud data warehouse, data lake, or data lakehouse. Designed to be modular.

IT 59

IT Data Warehouse Data Governance Data Lake 59

The Modern Data Company

MARCH 1, 2024

For today’s Chief Data Officers (CDOs) and data teams, the struggle is real. We’re drowning in data yet thirsting for actionable insights. We need a new approach, a paradigm shift that delivers data with the agility and efficiency of a speedboat – enter Data Products.

Database-centric 40

Database-centric Data Lake Government Retail 40

AltexSoft

MARCH 30, 2023

What is Databricks Databricks is an analytics platform with a unified set of tools for data engineering, data management , data science, and machine learning. It combines the best elements of a data warehouse, a centralized repository for structured data, and a data lake used to host large amounts of raw data.

Scala 64

Scala Data Lake BI Google Cloud 64