AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 87

Data Lake Analytics Snapshot Optimization 87

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

AWS Big Data

AUGUST 3, 2023

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need. Then we can query the data with Amazon Athena visualize it in Amazon QuickSight.

Data Lake 80

Data Lake Visualization Dashboards Insurance 80

IBM Big Data Hub

MAY 19, 2023

Furthermore, TDC Digital had not used any cloud storage solution and experienced latency and downtime while hosting the application in its data center. TDC Digital is excited about its plans to host its IT infrastructure in IBM data centers, offering better scalability, performance and security.

Unstructured Data 74

Unstructured Data Data Processing Manufacturing Data Lake 74

IBM Big Data Hub

FEBRUARY 2, 2023

In today’s world, data warehouses are a critical component of any organization’s technology ecosystem. The rise of cloud has allowed data warehouses to provide new capabilities such as cost-effective data storage at petabyte scale, highly scalable compute and storage, pay-as-you-go pricing and fully managed service delivery.

Data Warehouse 56

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 56

Sisense

OCTOBER 6, 2020

Despite its many uses, quantitative data presents two main challenges for a data-driven organization. First, data isn’t created in a uniform, consistent format. It’s generated by a host of sources in different ways. Advanced technology and new approaches are needed.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Sisense

NOVEMBER 12, 2020

While the organization of these layers has been refined over the years, the interoperability of the technologies, the myriad software, and orchestration of the systems make the management of these systems a challenge. Cloud data warehouses. with a cloud data warehouse is simple.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52