article thumbnail

Data Warehouse vs Big Data

Knowledge Hut

Two popular approaches that have emerged in recent years are data warehouse and big data. While both deal with large datasets, but when it comes to data warehouse vs big data, they have different focuses and offer distinct advantages.

article thumbnail

Prepare Your Unstructured Data For Machine Learning And Computer Vision Without The Toil Using Activeloop

Data Engineering Podcast

In this episode Davit Buniatyan, founder and CEO of Activeloop, explains why he is spending his time and energy on building a platform to simplify the work of getting your unstructured data ready for machine learning. Hightouch is the easiest way to sync data into the platforms that your business teams rely on.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

A new era of SQL-development, fueled by a modern data warehouse

Cloudera

SQL development is not a new concept. However, as the data warehousing world shifts into a fast-paced, digital, and agile era, the demands to quickly generate reports and help guide data-driven decisions are constantly increasing. Cloudera recently launched Cloudera Data Warehouse, a modern data warehousing solution.

article thumbnail

Cloudera Data Warehouse – A Partner Perspective

Cloudera

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Informatica’s Big Data Manager and Qlik’s acquisition of Podium Data are just 2 examples.

article thumbnail

Combining The Simplicity Of Spreadsheets With The Power Of Modern Data Infrastructure At Canvas

Data Engineering Podcast

Datafold built automated regression testing to help data and analytics engineers deal with data quality in their pull requests. Datafold shows how a change in SQL code affects your data, both on a statistical level and down to individual rows and values before it gets merged to production.

Metadata 130
article thumbnail

5 Layers of Data Lakehouse Architecture Explained

Monte Carlo

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. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.

article thumbnail

Data Lakehouse Architecture Explained: 5 Layers

Monte Carlo

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. The data lakehouse’s semantic layer also helps to simplify and open data access in an organization.