The Modern Data Company

MAY 10, 2023

Data governance and security: Evaluate the native security, data governance, and data quality management features. Wants to leverage the power of advanced analytics, AI, and machine learning on large volumes of raw data. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

The Modern Data Company

MAY 10, 2023

Data governance and security: Evaluate the native security, data governance, and data quality management features. Wants to leverage the power of advanced analytics, AI, and machine learning on large volumes of raw data. Data lakes offer a scalable and cost-effective solution.

Data Management 52

Data Management Data Lake Management Data Warehouse 52

AltexSoft

MARCH 14, 2023

Batch jobs are often scheduled to load data into the warehouse, while real-time data processing can be achieved using solutions like Apache Kafka and Snowpipe by Snowflake to stream data directly into the cloud warehouse. But this distinction has been blurred with the era of cloud data warehouses.

IT 59

IT Data Warehouse Data Governance Data Lake 59

Snowflake

MARCH 30, 2023

Collecting, cleaning, and organizing data into a coherent form for business users to consume are all standard data modeling and data engineering tasks for loading a data warehouse. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 83

Engineering Raw Data Data Science Scala 83

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

AltexSoft

AUGUST 29, 2023

In 2010, a transformative concept took root in the realm of data storage and analytics — a data lake. The term was coined by James Dixon , Back-End Java, Data, and Business Intelligence Engineer, and it started a new era in how organizations could store, manage, and analyze their data. Raw data store section.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

AUGUST 19, 2023

We’ll cover: What is a data platform? To make things a little easier, I’ve outlined the six must-have layers you need to include in your data platform and the order in which many of the best teams choose to implement them. The five must-have layers of a modern data platform Second to “how do I build my data platform?”,

Building 52

Building BI Data Lake Data Governance 52

Monte Carlo

APRIL 4, 2023

Today, when a data professional uses the term “data warehouse” they are likely referring to these cloud solutions that feature architectures with separate compute query engine and data storage. A data mesh might leverage one or several cloud data warehouses depending on how closely the organization adheres to the dogma.

Data Warehouse 52

Data Warehouse Data Governance Data Architecture 52

Knowledge Hut

JULY 31, 2023

It investigates how data mining algorithms can be utilized to discover hidden patterns, insights, and actionable knowledge from large datasets, aiding in decision-making and improving operational efficiency. They manage data access, monitor data quality, and enforce data protection measures.

Business Intelligence 52

Business Intelligence BI Data Mining Data Collection 52

AltexSoft

MAY 12, 2023

For example, developers can use Twitter API to access and collect public tweets, user profiles, and other data from the Twitter platform. Data ingestion tools are software applications or services designed to collect, import, and process data from various sources into a central data storage system or repository.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

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. 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.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

AltexSoft

JUNE 26, 2023

Data collection revolves around gathering raw data from various sources, with the objective of using it for analysis and decision-making. It includes manual data entries, online surveys, extracting information from documents and databases, capturing signals from sensors, and more. Find sources of relevant data.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

NOVEMBER 10, 2021

The DW nature isn’t the best fit for complex data processing such as machine learning as warehouses normally store task-specific data, while machine learning and data science tasks thrive on the availability of all collected data. Another type of data storage — a data lake — tried to address these and other issues.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

AltexSoft

SEPTEMBER 23, 2021

Data access layer unites all the access points connected to the data hub (transactional application, BI systems, machine learning training software, etc). Orchestration layer provides control over data integration, flows, transformations, and data governance. Data hub architecture. Azure Data Factory.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Monte Carlo

JUNE 14, 2023

In this post, we will help you quickly level up your overall knowledge of data pipeline architecture by reviewing: Table of Contents What is data pipeline architecture? Why is data pipeline architecture important? This is frequently referred to as a 5 or 7 layer (depending on who you ask) data stack like in the image below.

Data Pipeline 52

Data Pipeline Architecture Data Lake 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

ProjectPro

NOVEMBER 30, 2021

Now that we have understood how much significant role data plays, it opens the way to a set of more questions like How do we acquire or extract raw data from the source? How do we transform this data to get valuable insights from it? Where do we finally store or load the transformed data?

Process 52

Process Data Pipeline Data Warehouse AWS 52

Monte Carlo

JULY 30, 2020

Unlike traditional monolithic data infrastructures that handle the consumption, storage, transformation, and output of data in one central data lake, a data mesh supports distributed, domain-specific data consumers and views “data-as-a-product,” with each domain handling their own data pipelines.

IT 45

IT Data Lake Business Intelligence Data Architecture 45

ProjectPro

JANUARY 31, 2022

Provides Powerful Computing Resources for Data Processing Before inputting data into advanced machine learning models and deep learning tools, data scientists require sufficient computing resources to analyze and prepare it. They can also design and run data apps and securely share, gather, and commercialize real-time data.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Monte Carlo

AUGUST 31, 2023

Data pipelines can handle both batch and streaming data, and at a high-level, the methods for measuring data quality for either type of asset are much the same. For instance, in the late 2010s, Uber changed all data analysts’ titles to data scientists after an organizational restructure.

Data Lake 52

Data Lake Data Pipeline Unstructured Data Data Warehouse 52