AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Data warehouse vs. data lake in a nutshell.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Ascend.io

FEBRUARY 28, 2024

This process reduces noise in the data, which is crucial for the effectiveness of AI algorithms, especially in complex predictive models and deep learning applications. Such comprehensive metadata management is crucial in adhering to privacy and compliance standards, safeguarding AI operations against potential legal and ethical pitfalls.

Data Engineering 52

Data Engineering Data Engineer Engineering Metadata 52

Cloudera

OCTOBER 11, 2022

But it isn’t just aggregating data for models. Data needs to be prepared and analyzed. Different data types need different types of analytics – real-time, streaming, operational, data warehouses. And that data is likely in clouds, in data centers and at the edge.

Data Science 93

Data Science Aggregated Data Data Consulting 93

Cloudera

SEPTEMBER 15, 2022

The consumption of the data should be supported through an elastic delivery layer that aligns with demand, but also provides the flexibility to present the data in a physical format that aligns with the analytic application, ranging from the more traditional data warehouse view to a graph view in support of relationship analysis.

Data Lake 82

Data Lake Analytics Application Cloud Storage Architecture 82

Databand.ai

JUNE 28, 2023

Yet reality is of course more closely governed by Murphy’s law, and on the output side of the black box, you will often see a host of strange values and cryptic missing columns. Data engineers are scratching their heads and realizing that to correct, you must first observe. And why the discrepancy? See Databand in action Databand.ai

Data Pipeline 98

Data Pipeline Data Engineering Data Engineer Engineering 98

Rockset

AUGUST 2, 2023

For one, the company decided to invest in an API Insights Lab where customers and partners across suppliers, carriers, governments and insurance companies could use maritime data as part of their internal systems and workflows. As a result, Windward wanted an underlying data stack that took an API first approach.

Database-centric 52

Database-centric PostgreSQL Transportation Insurance 52

Cloudera

AUGUST 30, 2022

Data is the fuel that drives government, enables transparency, and powers citizen services. Citizens who have negative experiences with government services are less likely to use those services in the future. Modern data architectures. Deploying modern data architectures. Forrester ).

Data Architecture 78

Data Architecture Architecture Data Lake NoSQL 78

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 90

Data Lake Data Warehouse Cloud Unstructured Data 90

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

Towards Data Science

FEBRUARY 15, 2023

Data by itself has no value, it needs to be organized, standardized, and clean. Governance is needed. In this context, data management in an organization is a key point for the success of its projects involving data. One of the main aspects of correct data management is the definition of a data architecture.

Data Lake 76

Data Lake Data Warehouse Hadoop Data Architecture 76

Monte Carlo

APRIL 1, 2021

is whether to choose a data warehouse or lake to power storage and compute for their analytics. is whether to choose a data warehouse or lake to power storage and compute for their analytics. While data warehouses provide structure that makes it easy for data teams to efficiently operationalize data (i.e.,

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Cloudera

JUNE 30, 2022

With Cloudera’s vision of hybrid data , enterprises adopting an open data lakehouse can easily get application interoperability and portability to and from on premises environments and any public cloud without worrying about data scaling. Why integrate Apache Iceberg with Cloudera Data Platform?

Data Lake 87

Data Lake Business Intelligence Metadata Data Warehouse 87

Ascend.io

MARCH 14, 2023

We’re increasingly coming to realize that the rigid, monolithic architectures we’re currently using just don’t make the cut to store, organize, access, and use the ever-growing amounts of data. What Is a Data Mesh? It provides a more distributed, decentralized, and resilient approach to data management.

Government 52

Government Architecture Data Lake Data 52

Ascend.io

MARCH 14, 2023

We’re increasingly coming to realize that the rigid, monolithic architectures we’re currently using just don’t make the cut to store, organize, access, and use the ever-growing amounts of data. What Is a Data Mesh? It provides a more distributed, decentralized, and resilient approach to data management.

Government 52

Government Architecture Data Lake Data 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

Monte Carlo

NOVEMBER 21, 2022

Pro-tip: be sure to check out his talk from IMPACT: The Data Observability Summit. That gives a lot of credence to the idea you can look at Snowflake’s revenues as a proxy for what’s happening in the larger data ecosystem. billion in four years, which underscores the terrific demand there is for cloud data warehouses.

Data Engineering 52

Data Engineering Data Engineer Engineering Data Warehouse 52

Monte Carlo

JUNE 14, 2023

The modern data stack era , roughly 2017 to present data, saw the widespread adoption of cloud computing and modern data repositories that decoupled storage from compute such as data warehouses, data lakes, and data lakehouses. They also recently acquired Apache Flink , another streaming solution.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

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

ProjectPro

JANUARY 31, 2022

As the demand for big data grows, an increasing number of businesses are turning to cloud data warehouses. The cloud is the only platform to handle today's colossal data volumes because of its flexibility and scalability. Launched in 2014, Snowflake is one of the most popular cloud data solutions on the market.

Architecture 52

Architecture IT Data Warehouse Amazon Web Services 52

Advancing Analytics: Data Engineering

NOVEMBER 10, 2020

We have discussed in the past this idea of the lakehouse , the aspirational target of many analytics platforms these days of combining the huge power and potential of data lakes with the rigour, reliability and concurrency of a data warehouse. Essentially, we store data twice so that we can achieve the best of both worlds.

SQL 52

SQL BI Data Warehouse Data Lake 52

ProjectPro

OCTOBER 20, 2021

On that note, what is AI governance? AI Governance is a necessary evil. The four guideposts of AI Governance are as follows: Integrity The integrity and validity of the algorithm have to be justified by analyzing decision lineage and justification of what micro-decisions lead to the final output.

Machine Learning 52

Machine Learning Algorithm Government Data Science 52

Towards Data Science

APRIL 3, 2023

As part of this movement, Fivetran and dbt fundamentally altered the data pipeline from ETL to ELT. Hightouch interrupted SaaS eating the world in an attempt to shift the center of gravity to the data warehouse. Data is bigger and faster, but it’s also messier and less governed. No duplicate data storage.

Data Engineering 98

Data Engineering Data Engineer Engineering Data Warehouse 98

AltexSoft

MAY 12, 2023

There are several widely used unstructured data storage solutions such as data lakes (e.g., MongoDB, Cassandra), and big data processing frameworks (e.g., Also, modern cloud data warehouses and data lakehouses may be good options for the same purposes. Build data architecture.

Unstructured Data 59

Unstructured Data NoSQL Hadoop Data Lake 59

phData: Data Engineering

JULY 18, 2023

Why Migrate to a Modern Data Stack? With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Pipeline-centric Government Data 52

Cloudera

MAY 22, 2019

Although the program is technically in its seventh year, as the first joint awards program, this year’s Data Impact Awards will span even more use cases, covering even more advances in IoT, data warehouse, machine learning, and more. DATA SECURITY AND GOVERNANCE.

Pharmaceutical 55

Pharmaceutical Recruitment Machine Learning Metadata 55

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

DECEMBER 8, 2023

Enter: data provenance and data lineage. Data lineage is a visual tool that tracks the movement and transformations of data through various systems, processes, and applications. Data provenance is the record of metadata from data’s original sources, providing the historical context and authenticity of data.

Metadata 52

Metadata Data Data Warehouse Government 52

Monte Carlo

APRIL 20, 2023

Data is bigger and faster, but it’s also messier and less governed. Here are three examples of data quality related data lineage use cases. Preventing (or recovering from) unexpected schema changes A data lineage visualization. This is one of the most frequent data lineage use cases leveraged by Vox.

Data Warehouse 52

Data Warehouse BI Data Government 52

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

MAY 17, 2023

Data Warehouse (Or Lakehouse) Migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. “We Another common breaking schema change scenario is when data teams sync their production database with their data warehouse as is the case with Freshly.

Data 52

Data Data Pipeline Data Engineering Data Engineer 52

Monte Carlo

MAY 17, 2023

Data warehouse (or Lakehouse) migration 34. Integrate Data Stacks Post Merger 35. Know When To Fix Vs. Refactor Data Pipelines Improve DataOps Processes 37. “We Another common breaking schema change scenario is when data teams sync their production database with their data warehouse as is the case with Freshly.

Data Pipeline 52

Data Pipeline Data Data Engineering Data Engineer 52

Monte Carlo

JANUARY 23, 2023

But while most every company would consider themselves a “data-first” organization, not every data architecture is treated to the same level of democratization and scalability. In this post we’ll look at the dizzyingly buzzy data mesh and how it stacks up to the more traditional aggregated architectural approach of a data lake.

Data Lake 52

Data Lake Business Intelligence Unstructured Data Architecture 52

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. Why use a data mesh?

IT 45

IT Data Lake Business Intelligence Data Architecture 45