Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. There are two main options available, a data lake and a data warehouse. What is a Data Warehouse?

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

NOVEMBER 14, 2023

Over the last few months, Apache Iceberg has come to the forefront as a promising new open-source table format that removes many of the largest barriers to lakehouse adoption – namely, the high-latency and lack of OLTP (Online Transaction Processing) support afforded by Apache Hive. How Apache Iceberg tables structure metadata.

Data Lake 64

Data Lake Metadata Data Warehouse SQL 64

Data Engineering Podcast

NOVEMBER 27, 2022

Summary The data ecosystem has been growing rapidly, with new communities joining and bringing their preferred programming languages to the mix. This has led to inefficiencies in how data is stored, accessed, and shared across process and system boundaries. Atlan is the metadata hub for your data ecosystem.

Data Process 100

Data Process Process Metadata Business Intelligence 100

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 Business Intelligence Unstructured Data Architecture 52

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Data Engineering Podcast

FEBRUARY 19, 2023

Because of their complete ownership of your data they constrain the possibilities of what data you can store and how it can be used. Can you describe what Iceberg is and its position in the data lake/lakehouse ecosystem? For someone who wants to manage their data in Iceberg tables, what does the implementation look like?

IT 147

IT Data Lake Metadata Data Warehouse 147

ProjectPro

AUGUST 11, 2021

“Data Lake vs Data Warehouse = Load First, Think Later vs Think First, Load Later” The terms data lake and data warehouse are frequently stumbled upon when it comes to storing large volumes of data. Data Warehouse Architecture What is a Data lake?

Data Lake 52

Data Lake Data Warehouse Cloud Hadoop 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. Who has access to it?

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Monte Carlo

MAY 31, 2022

How we automate SQL lineage Developing data lineage for SQL is a much different process than developing Spark lineage. To retrieve data using SQL, a user would write and execute a query, which is then typically stored in a log. We knew it wouldn’t be easy, but beating the odds is indelible to our engineering culture.

Data Lake 52

Data Lake Building Scala Metadata 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4. …ok, so maybe they don’t say that. But they should! Storage layer 3. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

Monte Carlo

JANUARY 5, 2024

Data lakehouse architecture combines the benefits of data warehouses and data lakes, bringing together the structure and performance of a data warehouse with the flexibility of a data lake. Metadata layer 4. …ok, so maybe they don’t say that. But they should! Storage layer 3. API layer 5.

Architecture 52

Architecture Data Lake Metadata Unstructured Data 52

François Nguyen

MARCH 22, 2021

TL;DR After setting up and organizing the teams, we are describing 4 topics to make data mesh a reality. With this 3rd platform generation, you have more real time data analytics and a cost reduction because it is easier to manage this infrastructure in the cloud thanks to managed services. What you have to code is this workflow !

Technology 130

Technology Architecture Google Cloud Metadata 130

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

ProjectPro

FEBRUARY 8, 2023

In 2023, more than 5140 businesses worldwide have started using AWS Glue as a big data tool. For e.g., Finaccel, a leading tech company in Indonesia, leverages AWS Glue to easily load, process, and transform their enterprise data for further processing. AWS Glue automates several processes as well.

AWS 98

AWS Scala Metadata Data Lake 98

Snowflake

JULY 10, 2023

Announced at Summit, we’ve recently added to Snowpark the ability to process files programmatically, with Python in public preview and Java generally available. Data engineers and data scientists can take advantage of Snowflake’s fast engine with secure access to open source libraries for processing images, video, audio, and more.

Unstructured Data 40

Unstructured Data Python Process Scala 40

Precisely

JUNE 6, 2023

The group kicked off the session by exchanging ideas about what it means to have a modern data architecture. Atif Salam noted that as recently as a year ago, the primary focus in many organizations was on ingesting data and building data lakes. Sanjeev Mohan recommends frequent and ongoing experimentation.

Data Architecture 52

Data Architecture Architecture Metadata Data Lake 52

Data Engineering Weekly

MARCH 24, 2024

As we predicted in the key trends of 2023 about Apache Flink as a clear winner in the stream processing frameworks, we see Confluent offering Flink as a service. The author goes beyond comparing the tools to various offerings from streaming vendors in stream processing and Kafka protocol-supported systems.

Data Engineering 62

Data Engineering Data Engineer Engineering Metadata 62

Data Engineering Podcast

AUGUST 28, 2022

Atlan is the metadata hub for your data ecosystem. Instead of locking your metadata into a new silo, unleash its transformative potential with Atlan’s active metadata capabilities. RudderStack helps you build a customer data platform on your warehouse or data lake.

Data Engineering 100

Data Engineering Data Engineer MongoDB Metadata 100

LinkedIn Engineering

JULY 19, 2023

Open source data lakehouse deployments are built on the foundations of compute engines (like Apache Spark, Trino, Apache Flink), distributed storage (HDFS, cloud blob stores), and metadata catalogs / table formats (like Apache Iceberg, Delta, Hudi, Apache Hive Metastore). Tables are governed as per agreed upon company standards.

Big Data 78

Big Data Data Management Management Metadata 78

Towards Data Science

FEBRUARY 9, 2024

Streaming Kafka/ Confluent is king when it comes to data streaming, but working with streaming data introduces a number of new considerations beyond topics, producers, consumers, and brokers, such as serialization, schema registries, stream processing/transformation and streaming analytics.

Building 76

Building Transportation Data Lake Metadata 76

Towards Data Science

FEBRUARY 6, 2024

ERP and CRM systems are designed and built to fulfil a broad range of business processes and functions. This generalisation makes their data models complex and cryptic and require domain expertise. Searching for data Imagine being a data engineer/analyst tasked with identifying the top-selling products within your company.

Systems 76

Systems Raw Data Metadata Data Cleanse 76

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

The Modern Data Company

APRIL 15, 2024

The Role of a Data Model Explained Think of a data model as the ultimate organizer in the vast library of your company’s data. Its job, from its position near the end of the data processing line, is similar to that of a librarian who: Answers queries from various departments looking for specific insights.

Government 52

Government Metadata Data Data Lake 52

Snowflake

JANUARY 22, 2024

As part of that transition, Fidelity has consolidated its analytics data into its Enterprise Analytics Platform, which is engineered using the Snowflake Data Cloud, making it easier for teams and departments across the company to access the data they need. Historically, the platform was housed in physical servers.

Engineering 63

Engineering Data Lake Unstructured Data Metadata 63

Ascend.io

AUGUST 31, 2023

But the capabilities of the clouds have eclipsed traditional data architectures, and have upset the roles of data acquisition (“Extract”), logical processing (“Transform”), and populating a schema (“Load”). Still, these methods have been overshadowed by EtLT — the predominant approach reshaping today’s data landscape.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Towards Data Science

JULY 24, 2023

Our data warehouse would be down for 12 hours a day because we would regularly need to take it offline for data transformations and loading…The only word I can use to describe this process is painful.” Why are these things related, and more importantly, why should data leaders care? Take data governance for example.

Metadata 94

Metadata Data Warehouse Data Lake Data Science 94

Cloudera

JUNE 25, 2021

This blog post outlines detailed step by step instructions to perform Hive Replication from an on-prem CDH cluster to a CDP Public Cloud Data Lake. CDP Data Lake cluster versions – CM 7.4.0, Pre-Check: Data Lake Cluster. Understanding Ranger Policies in Data Lake Cluster. Runtime 7.2.8.

Cloud 73

Cloud Data Lake Cloud Storage Metadata 73

Monte Carlo

JUNE 26, 2023

Over the past decade, Databricks and Apache Spark™ not only revolutionized how organizations store and process their data, but they also expanded what’s possible for data teams by operationalizing data lakes at an unprecedented scale across nearly infinite use cases. billion in 2020 to $17.6

Data Lake 52

Data Lake Metadata Bytes Google Cloud 52

Monte Carlo

MAY 18, 2023

Depending on your requirements (more on that in the next section), it is prudent to evaluate open source data lineage tools alongside the several other types of platforms that provide data lineage capabilities. You may even already have access to one of them. The Spark data lake lineage example is helpful for context here.

Metadata 64

Metadata Data Lake Government Data Governance 64

Monte Carlo

JUNE 28, 2022

To help organizations realize the full potential of their data lake and lakehouse investments, Monte Carlo, the data observability leader, is proud to announce integrations with Delta Lake and Databricks’ Unity Catalog for full data observability coverage. billion in 2020 to 17.60 billion in 2020 to 17.60

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

Snowflake

JUNE 4, 2024

Supporting open storage architectures The AI Data Cloud is a single platform for processing and collaborating on data in a variety of formats, structures and storage locations, including data stored in open file and table formats.

Government 80

Government Data Ingestion Data PostgreSQL 80

ProjectPro

NOVEMBER 30, 2021

In extract-transform-load (ETL), data is obtained from multiple sources, transformed, and stored in a single data warehouse, with access to data analysts , data scientists , and business analysts for data visualization and statistical analysis model building, forecasting, etc.

Process 52

Process Data Pipeline Data Warehouse AWS 52

Cloudera

SEPTEMBER 23, 2020

Comprehensive auditing is provided to enable enterprises to effectively and efficiently meet their compliance requirements by auditing access and other types of operations across OpDB (through HBase). User, business classification of asset accessed. Policy outcome (access or deny). Policy outcome (access or deny).

Database 84

Database Data Lake Metadata Java 84

Monte Carlo

MAY 30, 2023

It’s designed to improve upon the performance and usability challenges of older data storage formats such as Apache Hive and Apache Parquet. Choose the right partitioning strategy Partitioning can significantly improve query performance by reducing the amount of data scanned.

Metadata 52

Metadata Raw Data Data Lake Data 52

Silectis

FEBRUARY 3, 2021

Data lineage refers to the entire lifecycle of a dataset from its sources of origin all the way to its current state. Within a data lake, data lineage becomes increasingly complex as the amount of data and number pipelines increases. As this process repeats itself, data lakes devolve into dreaded data swamps.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Lake 52

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? A data fabric offers unity in a formerly disconnected, incompatible data environment. Multiple benefits characterize the data fabric.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? A data fabric offers unity in a formerly disconnected, incompatible data environment. Multiple benefits characterize the data fabric.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52