As an organization facing business problems and dealing with data on a daily basis, the ability to build systems that can predict business outcomes becomes very important. This ability lets you solve problems and move faster by automating slow processes and embedding intelligence in your IT systems. But how do you make sure that all teams and individual decision makers in the organization are empowered to create these machine learning (ML) systems at scale, and without depending on other data science and data engineering teams? As a business user or data analyst, you’d like to build and use prediction systems based on the data that you analyze and process every day, without having to learn about hundreds of algorithms, training…
Category: AWS
Reposts from Amazon Web Services (AWS).
Amazon Kinesis Data Streams On-Demand – Stream Data at Scale Without Managing Capacity
Today we are launching Amazon Kinesis Data Streams On-demand, a new capacity mode. This capacity mode eliminates capacity provisioning and management for streaming workloads. Kinesis Data Streams is a fully-managed, serverless service for real-time processing of streamed data at a massive scale. Kinesis Data Streams can take any amount of data, from any number of sources, and scale up and down as needed. Creating a new data stream is easy, since we announced Kinesis Data Streams in November 2013. To get started, you only need to specify the number of shards with which you must provision your stream. Shards are the way to define capacity in Kinesis Data Streams. Each shard can ingest 1 MB/s and 1,000 records/second and egress…
Introducing Amazon Redshift Serverless – Run Analytics At Any Scale Without Having to Manage Data Warehouse Infrastructure
We’re seeing the use of data analytics expanding among new audiences within organizations, for example with users like developers and line of business analysts who don’t have the expertise or the time to manage a traditional data warehouse. Also, some customers have variable workloads with unpredictable spikes, and it can be very difficult for them to constantly manage capacity. With Amazon Redshift, you use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes. Today, I am happy to introduce the public preview of Amazon Redshift Serverless, a new capability that makes it super easy to run analytics in the cloud with high performance at any scale. Just load your data and start querying. There…
AWS Lake Formation – General Availability of Cell-Level Security and Governed Tables with Automatic Compaction
A data lake can help you break down data silos and combine different types of analytics into a centralized repository. You can store all of your structured and unstructured data in this repository. However, setting up and managing data lakes involve a lot of manual, complicated, and time-consuming tasks. AWS Lake Formation makes it easy to set up a secure data lake in days instead of weeks or months. Today, I am excited to share the general availability of some new features that simplify even further loading data, optimizing storage, and managing access to a data lake: Governed Tables – A new type of Amazon Simple Storage Service (Amazon S3) tables that makes it simple and reliable to ingest and…