DareData

JULY 5, 2023

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. For example, an industrial analytics team wants to use the logs from raw data. The Data Warehouse(s) facilitates data ingestion and enables easy access for end-users.

Data Lake 52

Data Lake Building Raw Data ETL Tools 52

WeCloudData

OCTOBER 19, 2021

By leveraging data engineering techniques combined with a cloud toolchain, WeCloudData helped a client achieve a continuous flow of current job market data with analytical capabilities and dashboards to drive the business forward and stay competitive.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

WeCloudData

OCTOBER 19, 2021

By leveraging data engineering techniques combined with a cloud toolchain, WeCloudData helped a client achieve a continuous flow of current job market data with analytical capabilities and dashboards to drive the business forward and stay competitive.

Consulting 52

Consulting Raw Data Data Lake Data Pipeline 52

Rockset

AUGUST 30, 2021

It becomes prohibitively complex and expensive to use a data warehouse to serve real-time analytics. Rockset: Real-time Analytics Built for the Cloud Rockset is doing for real-time analytics what Snowflake did for batch. But until this release, all these data sources involved indexing the incoming raw data on a record by record basis.

SQL 52

SQL Kafka MongoDB MySQL 52

ProjectPro

DECEMBER 7, 2021

Keeping data in data warehouses or data lakes helps companies centralize the data for several data-driven initiatives. While data warehouses contain transformed data, data lakes contain unfiltered and unorganized raw data.

Data Pipeline 52

Data Pipeline Architecture Kafka AWS 52

Monte Carlo

FEBRUARY 15, 2023

Since the inception of the cloud, there has been a massive push to store any and all data. On the surface, the promise of scaling storage and processing is readily available for databases hosted on AWS RDS, GCP cloud SQL and Azure to handle these new workloads. Cloud data warehouses solve these problems.

Data Warehouse 52

Data Warehouse Unstructured Data AWS Business Intelligence 52

ProjectPro

FEBRUARY 8, 2023

But this data is not that easy to manage since a lot of the data that we produce today is unstructured. In fact, 95% of organizations acknowledge the need to manage unstructured raw data since it is challenging and expensive to manage and analyze, which makes it a major concern for most businesses. How Does AWS Glue Work?

AWS 98

AWS Scala Metadata Data Lake 98