Monte Carlo

FEBRUARY 21, 2023

Enter data fabric: a data management architecture designed to serve the needs of the business, not just those of data engineers. A data fabric is an architecture and associated data products that provide consistent capabilities across a variety of endpoints spanning multiple cloud environments.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Data Engineering Podcast

SEPTEMBER 23, 2018

Using the metaphor of a museum curator carefully managing the precious resources on display and in the vaults, he discusses the various layers of an enterprise data strategy. How do you define data curation? How does the size and maturity of a company affect the ways that they architect and interact with their data systems?

Data Lake 100

Data Lake Data Warehouse Data Architecture Architecture 100

Databand.ai

AUGUST 30, 2023

DataOps is a collaborative approach to data management that combines the agility of DevOps with the power of data analytics. It aims to streamline data ingestion, processing, and analytics by automating and integrating various data workflows.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

AltexSoft

FEBRUARY 11, 2023

Data architecture is the organization and design of how data is collected, transformed, integrated, stored, and used by a company. Bad data management be like, Source: Makeameme Data architects are sometimes confused with other roles inside the data science team.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Data Engineering Podcast

JUNE 19, 2022

Summary Metadata is the lifeblood of your data platform, providing information about what is happening in your systems. In order to level up their value a new trend of active metadata is being implemented, allowing use cases like keeping BI reports up to date, auto-scaling your warehouses, and automated data governance.

Metadata 130

Metadata MongoDB Scala MySQL 130

Cloudera

FEBRUARY 16, 2022

In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. Each project consists of a declarative series of steps or operations that define the data science workflow.

Machine Learning 81

Machine Learning Algorithm Government Metadata 81

Cloudera

NOVEMBER 10, 2021

It provides a centralized platform to define, administer and manage security policies consistently across all Hadoop components that Sentry protected, as well as additional services in the Apache Hadoop ecosystem like Apache HBase, YARN, Apache NiFi. Access requests go back to Sentry Server each time for validation.

Hadoop 74

Hadoop SQL Database Kafka 74

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. Image courtesy of Dremio.

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

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

Data Engineering Podcast

NOVEMBER 26, 2023

In this episode Tobias Macey shares his thoughts on the challenges that he is facing as he prepares to build the next set of architectural layers for his data platform to enable a larger audience to start accessing the data being managed by his team. Data lakes are notoriously complex.

Architecture 147

Architecture Data Lake High Quality Data SQL 147

Cloudera

MARCH 23, 2022

The table information (such as schema, partition) is stored as part of the metadata (manifest) file separately, making it easier for applications to quickly integrate with the tables and the storage formats of their choice. Simplify data management . 3: Open Performance. The *Any*-house.

Metadata 88

Metadata Data Architecture BI Machine Learning 88

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

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

Towards Data Science

JULY 24, 2023

A decade later, a considerable amount of innovation in the data management industry is revolving around how different data platforms are coupling or decoupling storage and compute (don’t worry I include examples in the next section). Why are these things related, and more importantly, why should data leaders care?

Metadata 96

Metadata Data Warehouse Data Lake Data Science 96

Ascend.io

JULY 19, 2023

But something about data mesh feels different, doesn’t it? For one, data mesh tackles the real headaches caused by an overburdened data lake and the annoying game of tag that’s too often played between the people who make data, the ones who use it, and everyone else caught in the middle.

Data Governance 40

Data Governance Government Metadata Data 40

AltexSoft

NOVEMBER 23, 2021

If the transformation step comes after loading (for example, when data is consolidated in a data lake or a data lakehouse ), the process is known as ELT. You can learn more about how such data pipelines are built in our video about data engineering. Abstraction layer.

Process 69

Process Data Lake Metadata Data Warehouse 69

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

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

The Modern Data Company

JANUARY 17, 2023

Leaders Can Easily Bring the CDP Under Federated Governance CDPs ingest data through both governed and ungoverned channels. These include internal data lakes, apps (1st or 3rd party), web SDK, internal or 3rd-party databases, and even spreadsheets generated within the marketing department.

Metadata 59

Metadata Government Data Lake Data 59

Ascend.io

MARCH 14, 2023

Zhamak Dehghani first introduced the idea of the data mesh in 2019 as a better alternative to the monolithic data lake and its predecessor, the data warehouse. Simply put, a data mesh is a platform architecture — a philosophy of sorts — that separates data into domains and defines the responsibilities of each.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

Zhamak Dehghani first introduced the idea of the data mesh in 2019 as a better alternative to the monolithic data lake and its predecessor, the data warehouse. Simply put, a data mesh is a platform architecture — a philosophy of sorts — that separates data into domains and defines the responsibilities of each.

Government 52

Government Architecture Data Lake Data 52

ProjectPro

FEBRUARY 8, 2017

In 2017, big data platforms that are just built only for hadoop will fail to continue and the ones that are data and source agnostic will survive. Organizations are embarking on data lake strategy for applications that are centralized and for applications coming together on a single central platform.

Big Data 40

Big Data Hadoop Data Lake Data Governance 40

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

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. Based on Tecton blog So is this similar to data engineering pipelines into a data lake/warehouse?

Engineering 81

Engineering Raw Data Data Science Scala 81

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. So, why is data integration such a big deal?

Data Integration 52

Data Integration Hadoop Data Warehouse Data Lake 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

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.

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

AltexSoft

MAY 12, 2023

Unstructured data refers to information that lacks a predefined format or organization. In contrast, big data refers to large volumes of structured and unstructured data that are challenging to process, store, and analyze using traditional data management tools. Invest in data governance.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Cloudera

OCTOBER 7, 2021

The concept of the data mesh architecture is not entirely new; Its conceptual origins are rooted in the microservices architecture, its design principles (i.e., need to integrate multiple “point solutions” used in a data ecosystem) and organization reasons (e.g., difficulty to achieve cross-organizational governance model).

Architecture 121

Architecture Metadata Government Kafka 121

Monte Carlo

JULY 18, 2023

A decade later, a considerable amount of innovation in the data management industry is revolving around how different data platforms are coupling or decoupling storage and compute (don’t worry I include examples in the next section). Why are these things related, and more importantly, why should data leaders care?

Metadata 52

Metadata Data Warehouse Data Lake Government 52

Monte Carlo

JANUARY 12, 2024

Google recently announced that PubSub can directly stream into BigQuery as well as the launch of Dataflow Prime , an upgraded version of their managed streaming analytics service. On the data lake side, Databricks has launched Unity Catalog to help bring more metadata, structure, and governance to data assets.

Big Data 59

Big Data Data Analytics Data Science Data Lake 59

Monte Carlo

JULY 18, 2023

A decade later, a considerable amount of innovation in the data management industry is revolving around how different data platforms are coupling or decoupling storage and compute (don’t worry I include examples in the next section). Why are these things related, and more importantly, why should data leaders care?

Metadata 40

Metadata Data Warehouse Data Lake Government 40

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. Secure data exchange takes on much greater importance.

Cloud 72

Cloud Cloud Computing Metadata Data Governance 72

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 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. Designed to be modular.

IT 59

IT Data Warehouse Data Governance Data Lake 59