Rockset

APRIL 18, 2023

Organizations have continued to accumulate large quantities of unstructured data, ranging from text documents to multimedia content to machine and sensor data. Comprehending and understanding how to leverage unstructured data has remained challenging and costly, requiring technical depth and domain expertise.

Unstructured Data 105

Unstructured Data Metadata Machine Learning SQL 105

DareData

JANUARY 30, 2023

Our goal is to help data scientists better manage their models deployments or work more effectively with their data engineering counterparts, ensuring their models are deployed and maintained in a robust and reliable way. Examples of technologies able to aggregate data in data lake format include Amazon S3 or Azure Data Lake.

Data Engineer 52

Data Engineer Data Engineering NoSQL Engineering 52

Striim

OCTOBER 11, 2024

In contrast, traditional data pipelines often require significant manual effort to integrate various external tools for data ingestion , transfer, and analysis. Additionally, legacy systems frequently struggle with diverse data types, such as structured, semi-structured, and unstructured data.

Data Pipeline 52

Data Pipeline MongoDB Unstructured Data Data Lake 52

Monte Carlo

FEBRUARY 15, 2023

Data can be loaded in batches or can be streamed in near real-time. Structured, semi-structured, and unstructured data can be loaded. Can a data warehouse store unstructured data? Yes, data warehouses can store unstructured data as a blob datatype.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

DareData

JULY 5, 2023

We've seen this happen in dozens of our customers: data lakes serve as catalysts that empower analytical capabilities. If you work at a relatively large company, you've seen this cycle happening many times: Analytics team wants to use unstructured data on their models or analysis. And what is the reason for that?

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

ProjectPro

FEBRUARY 8, 2023

Create The Connector for Source Database The first step is having the source database, which can be any S3, Aurora, and RDS that can hold structured and unstructured data. Glue works absolutely fine with structured as well as unstructured data.

AWS 98

AWS Scala Metadata Data Lake 98

ProjectPro

OCTOBER 28, 2015

Apache Hadoop is synonymous with big data for its cost-effectiveness and its attribute of scalability for processing petabytes of data. Data analysis using hadoop is just half the battle won. Getting data into the Hadoop cluster plays a critical role in any big data deployment. then you are on the right page.

ETL Tools 52

ETL Tools Hadoop Relational Database Unstructured Data 52