Ascend.io

AUGUST 31, 2023

In the dynamic world of data, many professionals are still fixated on traditional patterns of data warehousing and ETL, even while their organizations are migrating to the cloud and adopting cloud-native data services. Source : A stream of sensor data represented as a directed acyclic graph.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Databand.ai

AUGUST 30, 2023

A DataOps architecture is the structural foundation that supports the implementation of DataOps principles within an organization. It encompasses the systems, tools, and processes that enable businesses to manage their data more efficiently and effectively. As a result, they can be slow, inefficient, and prone to errors.

Architecture 52

Architecture Data Ingestion Data Governance Data Cleanse 52

Cloudera

SEPTEMBER 15, 2022

The gathering in 2022 marked the sixteenth year for top data and analytics professionals to come to the MIT campus to explore current and future trends. A key area of focus for the symposium this year was the design and deployment of modern data platforms. What is a data fabric? What’s a trend you see on the horizon? .

Data Lake 81

Data Lake Analytics Application Cloud Storage Architecture 81

Rockset

APRIL 26, 2023

In this post, we’ll get to the details: how does one design an RTA system? We’ve noticed many common patterns across streaming data architectures and we’ll be sharing a blueprint for three of the most popular: anomaly detection, IoT, and recommendations. This could be a cloud data warehouse, a data lake, or a database.

Architecture 52

Architecture Transportation Data Lake Insurance 52

Silectis

JANUARY 3, 2021

Big Query Google’s cloud data warehouse. 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.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

SEPTEMBER 29, 2023

By combining data from various structured and unstructured data systems into structures, Microsoft Azure Data Engineers will be able to create analytics solutions. Why Should You Get an Azure Data Engineer Certification? Then, you can create analytical layer serving designs.

Certification 52

Certification Data Engineering Data Engineer Engineering 52

Monte Carlo

MAY 14, 2024

As organizations seek greater value from their data, data architectures are evolving to meet the demand — and table formats are no exception. At its core, a table format is a sophisticated metadata layer that defines, organizes, and interprets multiple underlying data files.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Knowledge Hut

NOVEMBER 28, 2023

With a plethora of new technology tools on the market, data engineers should update their skill set with continuous learning and data engineer certification programs. What do Data Engineers Do? Technical Data Engineer Skills 1.Python This can be easier when you are using existing cloud services.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Cloudera

AUGUST 21, 2020

Data-in-motion is predominantly about streaming data so enterprises typically have two different ways or binary ways of looking at data. The governance aspect is perhaps even more important and businesses need to be able to understand where the data comes from.

Banking 61

Banking Kafka Cloud Storage Government 61

Snowflake

NOVEMBER 2, 2023

Over the years, the technology landscape for data management has given rise to various architecture patterns, each thoughtfully designed to cater to specific use cases and requirements. Each of these architectures has its own unique strengths and tradeoffs.

Data Lake 91

Data Lake Data Warehouse Cloud Unstructured Data 91

Cloudera

AUGUST 30, 2022

Modern data architectures. To eliminate or integrate these silos, the public sector needs to adopt robust data management solutions that support modern data architectures (MDAs). Towards Data Science ). Solutions that support MDAs are purpose-built for data collection, processing, and sharing.

Data Architecture 77

Data Architecture Architecture Data Lake NoSQL 77

Data Engineering Podcast

SEPTEMBER 1, 2021

Summary The Presto project has become the de facto option for building scalable open source analytics in SQL for the data lake. That leaves DataOps reactive to data quality issues and can make your consumers lose confidence in your data. lets you identify data quality issues and their root causes from a single dashboard.

Data Lake 100

Data Lake Cloud AWS SQL 100

Data Engineering Podcast

JUNE 17, 2023

By incorporating column-level lineage in the data modeling process it encourages a more robust and well-informed design. In this episode Satish Jayanthi explores the benefits of incorporating column-aware tooling in the data modeling process. What are some of the ways that that information can be fed into other contexts?

Data Lake 130

Data Lake Metadata Data Architecture Machine Learning 130

Cloudera

MARCH 23, 2022

In fact, we recently announced the integration with our cloud ecosystem bringing the benefits of Iceberg to enterprises as they make their journey to the public cloud, and as they adopt more converged architectures like the Lakehouse. Iceberg is designed to be open and engine agnostic allowing datasets to be shared.

Metadata 90

Metadata Data Architecture BI Machine Learning 90

Cloudera

NOVEMBER 17, 2022

The Solution: CDP Private Cloud brings a next-generation hybrid architecture with cloud-native benefits to HBL’s data platform. HBL started their data journey in 2019 when data lake initiative was started to consolidate complex data sources and enable the bank to use single version of truth for decision making.

Banking 83

Banking Management Data Lake Professional Services 83

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? What is data pipeline architecture? Zero ETL is a bit of a misnomer.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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

Data Engineering Weekly

JANUARY 15, 2023

SiliconANGLE theCUBE: Analyst Predictions 2023 - The Future of Data Management By far one of the best analyses of trends in Data Management. 2023 predictions from the panel are; Unified metadata becomes kingmaker. The blog narrates the causal machine-learning approach in designing promotional artwork for their TV shows.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

AltexSoft

OCTOBER 30, 2021

Data scientists need to have precise domain knowledge to extract the most relevant features for a model to use. Feature engineering is one of the most important and time consuming parts of a data scientist’s job. Data scientists are well versed in algorithms and data-related problems to be able to make a solid choice.

Data Engineering 98

Data Engineering Data Engineer Engineering Machine Learning 98

AltexSoft

JULY 19, 2022

In the last few decades, we’ve seen a lot of architectural approaches to building data pipelines , changing one another and promising better and easier ways of deriving insights from information. There have been relational databases, data warehouses, data lakes, and even a combination of the latter two.

Architecture 52

Architecture Data Lake Medical Datasets 52

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The final step is designing a data solution and its implementation. DataOps Project Design and Implementation. Figure 2: Example data pipeline with DataOps automation.

Engineering 62

Engineering BI Business Analyst Metadata 62

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

JANUARY 31, 2023

Data Storage: The next step after data ingestion is to store it in HDFS or a NoSQL database such as HBase. HBase storage is ideal for random read/write operations, whereas HDFS is designed for sequential processes. Data Processing: This is the final step in deploying a big data model. No reliability exists.

Big Data 52

Big Data Hadoop AWS Relational Database 52

ProjectPro

OCTOBER 20, 2021

BERT (Bidirectional Encoder Representations from Transformers): BERT is designed to pre-train deep bidirectional representations. Data Integration at Scale Most data architectures rely on a single source of truth. Having multiple data integration routes helps optimize the operational as well as analytical use of data.

Machine Learning 52

Machine Learning Algorithm Government Data Science 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., Hadoop, Apache Spark).

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

Cloudera

OCTOBER 7, 2021

Introduction to the Data Mesh Architecture. 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., Data and Metadata: Data inputs and data outputs produced based on the application logic.

Architecture 123

Architecture Metadata Government Kafka 123

Monte Carlo

JANUARY 23, 2023

When it comes to the data community, there’s always a debate broiling about something— and right now “data mesh vs data lake” is right at the top of that list. In this post we compare and contrast the data mesh vs data lake to illustrate the benefits of each and help discover what’s right for your data platform.

Data Lake 52

Data Lake Unstructured Data Business Intelligence Architecture 52

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

Monte Carlo

JULY 30, 2020

In the age of self-service business intelligence , nearly every company considers themselves a data-first company, but not every company is treating their data architecture with the level of democratization and scalability it deserves. Your company, for one, views data as a driver of innovation. You will not regret it).

IT 45

IT Data Lake Business Intelligence Data Architecture 45