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8 Top AWS Migration Tools & Best Practices

Migrating to and from Amazon Web Services (AWS) is a common but tricky endeavor. Many moving parts and technical and security aspects need to be considered. AWS provides several of its own tools to simplify the migration process, but there are also several third-party products that can support the AWS migration process. This guide will walk you through some of the best options on the market, their pros and cons, and what features may be useful for your particular migration project.

Remodel Your Oracle Cloud Data with a Data Lakehouse

Continued global digitalization is creating huge quantities of data for modern organizations. To have any hope of generating value from growing data sets, enterprise organizations must turn to the latest technology. You’ve heard of data warehouses, and probable data lakes, but now, the data lakehouse is emerging as the new corporate buzzword. But what is a data lakehouse and how can you make the most of it to transform your Oracle Cloud data for advanced reporting and analytics?

ChatGPT Models: Choosing the Right Fit for Databox Analytics

At Databox, our mission is to help growing businesses leverage their data to make better decisions and improve their performance. We envision a future where every company, no matter the size, can harness its existing data to create more accurate marketing plans, sales goals, budget planning, and more.

Cloudera and AWS | Delivering New Generative AI Use Cases and Cutting-edge Analytics

AWS and Cloudera share a culture of customer obsession. Together Cloudera and AWS make it easier for customers to move to the cloud due to the deep technical integration. Our most recent collaboration is around the integration of generative AI with Amazon Bedrock which helps customers innovate with a modern data architecture to create new business use cases and leverage cutting-edge analytics. AWS executive David Littlewood, Head of Data and Analytics ISV Partnerships, discuss how collaborating with Cloudera benefits customers along their cloud migration and modern architecture journey.

Next-Level Apps with Snowpark Container Services and Snowflake Native Apps

The enterprise app market has been growing faster than ever before, due to the recent spike in demand for AI / ML workloads. These new types of apps operate over large sets of data, have increasingly higher compute demands, require strict data privacy protections, provide very sophisticated web experiences, and need to be secure at all stages of their life cycles. While such apps are being created at a very fast pace, there are two main challenges.

Data Wrangling vs. ETL: What's the Difference?

In data engineering and analytics, effectively wrangling data is not just a skill but a necessity. Large volumes of complex data have grown exponentially as businesses and technologies evolve. This surge has brought two critical processes in data management to the front line: Data Wrangling and Extract, Transform, Load (ETL). Understanding these processes is pivotal for any organization leveraging data for a strategic advantage.

Open Data Lakehouse for Private Cloud Ozone Snapshots

One of the features of the Open Data Lakehouse for Private Cloud is the Ozone compatibility. The snapshot feature for Apache Ozone object store enables you to take a point-in-time consistent image of a given bucket. This feature allows you to have data protection and backup, replication and disaster recovery, and an efficient way to find changes since last replication. Snapshots also help to meet Compliance requirements and have a stable source image for replication.