Systems | Development | Analytics | API | Testing

Datastream, a serverless database replication service, has integrated with Terraform to enhance app modernization, data analytics and ML pipelines.

It’s been a rollercoaster ride for everyone over the last few years, with particular pressure on Chief Financial Officers (CFOs) to support CEOs steering their organizations through things none of us expected to experience in our lifetime. Unfortunately, with the financial markets going into turmoil over the last few months and consumers of all shapes and sizes starting to cut back on spending, the uncertainty isn’t going to stop anytime soon.

Every day in the US thousands of legitimate prescriptions for the opioid class of pharmaceuticals are written to mitigate acute pain during post-operation recovery, chronic back and neck pain, and a host of other cases where patients experience moderate-to-severe discomfort.

10 years ago, it would be ridiculous for people to believe that someday they would be able to use their faces to unlock their phones. That’s because it had been extremely difficult to create cartoon characters without profound drawing skills – but now we can easily turn photos into cartoon characters. Struggling with parallel parking? No worries, because self-parking systems are becoming standard equipment in vehicles.

In a fast-paced world that produces more data than it can ingest, the right Python ETL tool makes all the difference. But not all Python tools are made the same. Some Python ETL tools are great for writing parallel load jobs for data warehousing, others are specialized for unstructured data extraction. In this article, we’ll explore the 7 best tools for ETL tasks and what business requirements they help you fulfill: Let’s dive right into the best tools and see how they compare.

By Jason Bloomberg, President, Intellyx Part 2 of the Demystifying Data Observability Series for Unravel Data In part one of this series, fellow Intellyx analyst Jason English explained the differences between DevOps and DataOps, drilling down into the importance of DataOps observability. The question he left open for this article: how did we get here? How did DevOps evolve to what it is today, and what parallels or differences can we find in the growth of DataOps?

Extract, Transform, Load (ETL), and Extract, Load, Transform (ELT) pipelines are standard data management techniques among data engineers. Indeed, organizations have long been using these processes to create effective data models. However, there has recently been a remarkable rise in the use of Software-as-a-Service (SaaS) based customer relationship management (CRM) apps, such as Salesforce, Zendesk, Hubspot, Zoho, etc., to store and analyze customer data.

Today Snowflake is officially launching the Telecom Data Cloud. Snowflake’s newest Data Cloud helps telecommunications service providers break down data silos within the business and across the ecosystem, allowing organizations to easily and securely access data in near real time, enrich it with machine learning models, and then share and analyze it to drive better decision-making.

Cloudera’s SQL Stream Builder (SSB) is a versatile platform for data analytics using SQL. As apart of Cloudera Streaming Analytics it enables users to easily write, run, and manage real-time SQL queries on streams with a smooth user experience, while it attempts to expose the full power of Apache Flink. SQL has been around for a long time, and it is a very well understood language for querying data.