Last year, we announced the general availability of RStudio on Amazon SageMaker, the industry's first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) and analytics solutions in R at scale. Many of the RStudio on SageMaker users are also users of Amazon Redshift, a fully managed, petabyte-scale, massively parallel data warehouse for data storage and analytical workloads. It makes it fast, simple, and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. The use of RStudio on SageMaker and Amazon Redshift can be helpful for efficiently performing analysis on large data sets in the cloud.

Amazon Redshift is a quick, totally managed cloud knowledge warehouse database that makes it cost-effective to investigate your knowledge utilizing normal SQL and enterprise intelligence instruments. Amazon Redshift permits you to analyze structured and semi-structured knowledge and seamlessly question knowledge lakes and operational databases, utilizing AWS designed {hardware} and automatic machine studying (ML)-based tuning to ship top-tier price-performance at scale. Though Amazon Redshift offers glorious value efficiency out of the field, it presents further optimizations that may enhance this efficiency and help you obtain even sooner question response instances out of your knowledge warehouse. For instance, you may bodily tune tables in an information mannequin to reduce the quantity of knowledge scanned and distributed inside a cluster, which accelerates operations corresponding to desk joins and range-bound scans. Amazon Redshift now automates this tuning with the computerized desk optimization (ATO) function.

Organizations of all sizes and across all industries gather and analyze metrics or key performance indicators (KPIs) to help their businesses run effectively and efficiently. Operational metrics are used to evaluate performance, compare results, and track relevant data to improve business outcomes. For example, you can use operational metrics to determine application performance (the average time it takes to render a page for an end user) or application availability (the duration of time the application was operational). One challenge that most organizations face today is detecting anomalies in operational metrics, which are key in ensuring continuity of IT system operations. Traditional rule-based methods are manual and look for data that falls outside of numerical ranges that have been arbitrarily defined.

Dataiku is going downstream with a new product today called Dataiku Online. As the name suggests, Dataiku Online is a fully managed version of Dataiku. It lets you take advantage of the data science platform without going through a complicated setup process that involves a system administrator and your own infrastructure. If you're not familiar with Dataiku, the platform lets you turn raw data into advanced analytics, run some data visualization tasks, create data-backed dashboards and train machine learning models. In particular, Dataiku can be used by data scientists, but also business analysts and less technical people.

Amazon Redshift ML allows data analysts, developers, and data scientists to train machine learning (ML) models using SQL. In previous posts, we demonstrated how customers can use the automatic model training capability of Amazon Redshift to train their classification and regression models. Redshift ML provides several capabilities for data scientists. It allows you to create a model using SQL and specify your algorithm as XGBoost. It also lets you bring your pre-trained XGBoost model into Amazon Redshift for local inference.

AI Daily Roundup starts today! We are covering the top updates from around the world. The updates will feature state-of-the-art capabilities in artificial intelligence, Machine Learning, Robotic Process Automation, Fintech and human-system interactions. We will cover the role of AI Daily Roundup and their application in various industries and daily lives. Datadobi, the global leader in unstructured data management software, announced it has been selected by award-winning solutions provider, Computex Technology Solutions, to migrate the data of a business-critical application for one of the largest financial and professional services providers in the world.

In the current age of cloud computing, there is now a multitude of mature services available -- offering security, scalability, and reliability for many business computing needs. What was once a colossal undertaking to build a data center, install server racks, and design storage arrays has given way to an entire marketplace of services that are always just a click away. One leader in that marketplace is Amazon Web Services, which consists of 175 products and services in a vast catalog that provides cloud storage, compute power, app deployment, user account management, data warehousing, tools for managing and controlling Internet of Things devices, and just about anything you can think of that a business needs. AWS really grew in popularity and capability over the last decade. One reason is that AWS is so reliable and secure.

DataSunrise, in their own words: DataSunrise is a database security software company that offers a breadth of security solutions, including data masking (dynamic and static masking), activity monitoring, database firewalls, and sensitive data discovery for various databases. The goal is to protect databases against external and internal threats and vulnerabilities. Customers often choose DataSunrise Database Security because it gives them unified control and a single-user experience when protecting different database engines that run on AWS, including Amazon Redshift, Amazon Aurora, all Amazon RDS database engines, Amazon DynamoDB, and Amazon Athena, among others. DataSunrise Security Suite is a set of tools that can protect and audit PII data in Amazon Redshift. DataSunrise offers passive security with data auditing in addition to active data and database security.

Inawisdom was engaged by Aramex, a global provider of logistics and transportation solutions, to support a digital transformation by enhancing the customer experience and digitizing the end-to-end shipment journey. "We are shifting increasingly to be an e-commerce company, and our vision is to be an innovative e-commerce provider that provides a revolutionary customer experience," says Mohammed Sleeq, chief digital officer at Aramex. "We wanted to give our customers a more accurate, instant prediction of delivery time, and we knew Inawisdom and AWS would enable us to do what we wanted to accomplish." To realize its transformation goals, Aramex chose Inawisdom as a partner to accelerate the delivery of an AWS cloud-native data science platform to deploy machine learning models into production. Inawisdom helped Aramex deploy the RAMP platform, which takes advantage of Amazon SageMaker and other key AWS services.

HERNDON, Va.--(BUSINESS WIRE)--47Lining, a REAN Cloud company, announced today that it has achieved Amazon Web Services (AWS) Machine Learning (ML) Competency status. This designation recognizes 47Lining for its consulting practice focused on helping customers establish real-time, predictive and statistical modeling results for use cases like real-time dashboards, industrial process optimization, customer churn, propensity modeling, content recommendation and fraud detection. Achieving the AWS ML Competency differentiates 47Lining as an AWS Partner Network (APN) member that has built solutions that help organizations solve their data challenges, enable machine learning and data science workflows or offer SaaS/API based capabilities that enhance end applications with machine intelligence. Attaining the AWS ML Competency demonstrates to customers that 47Lining has validated expertise and ML experience on AWS. "Achieving AWS ML Competency status recognizes 47Lining's proven track record of working with customers to enable widespread use of predictive and real-time analytics," said Mick Bass, Senior Vice President of REAN Cloud's Big Data Practice.