Tag: Big Data

Feed: AWS Big Data Blog. In May 2020, we announced the general availability of real-time anomaly detection for Elasticsearch. With that release we leveraged the Random Cut Forest (RCF) algorithm to identify anomalous behaviors in the multi-dimensional data streams generated by Elasticsearch queries. We focused on aggregation first, to enable our users to quickly and accurately detect anomalies in their data streams. However, consider the example data in the following table. timestamp avg. latency region 12:00 pm 3.1 Seattle 12:00 pm 4.1 New York 12:00 pm 5.9 Berlin 12:01 pm 2.6 Seattle 12:01 pm 5.3 New York 12:01 pm 5.8 ... Read More

Feed: AWS Big Data Blog. AWS Glue provides a serverless environment to prepare (extract and transform) and load large amounts of datasets from a variety of sources for analytics and data processing with Apache Spark ETL jobs. This posts discusses a new AWS Glue Spark runtime optimization that helps developers of Apache Spark applications and ETL jobs, big data architects, data engineers, and business analysts scale their data processing and batch jobs running on AWS Glue automatically. Customers use Spark for a wide variety of ETL and analytics workloads on datasets with diverse characteristics. They want to ensure fast and ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Rishabh Sinha. Across industries and enterprises, AI has been the key growth driver, and this is mainly due to the services offered under this technology umbrella. Every industry is now witnessing enhancements in business processes, costs, and efficiency due to AI's introduction in their field. Depending on the industry, AI offers something unique and has helped the key decision-makers to make fast and accurate decisions based on various implementation solutions. Talking particularly about the financial sector, the insurance industry has already deployed AI in their domain. An online report states that ... Read More

Feed: Big Data Made Simple. Author: Justas Markus. Are you uncertain whether your Macbook is as secure as it can be? Given how many threats are out there, it would probably be worth your while to take some time and make adjustments to how you have been using the computer until now.Read the methods below and create a strategy to improve the overall security of the computer. However, be sure not to abandon it because it will come back to bite you back.Method #1 – Install Reliable Antivirus SoftwareStart with getting antivirus software. The important thing is to have a ... Read More

Feed: Big Data Made Simple. Author: Lidia Hovhannisyan. The business environment is currently depicted as a highly competitive one, and to survive, one must come up with ingenious tactics to remain relevant. The current era of big data catches many business owners by surprise, with overwhelming volumes of information. But to remain relevant in their field, these company executives need to develop a way to understand and take full control of such information to derive the best value for their organization. For a person looking to make data-driven decisions, other than relying solely on their gut, you might find it useful ... Read More

Feed: Big Data Made Simple. Author: Gary Wilkinson. Remote work is becoming more common, and companies need to find ways to maintain face-to-face contact, so the business still operates, and work gets done. Through video conferencing apps, companies can start hosting remote online meetings with their teams. Benefits of video conferencing include:Team members less likely to multitask on a videoSeeing a real face makes a genuine connectionIt’s easier to get you to point across on the videoIt makes it easier to complete tasksMany companies are taking advantage of the video conferencing software and using it for everything. The rise of ... Read More

Feed: Big Data Made Simple. Author: Guest. Several customer experience trends indicate consumers have a high set of expectations from support teams. They expect a quick response, faster resolution, and superb experience. To meet these demands and ensure meaningful conversations, firms need to implement the best ticketing system and practices. Here’re tried and tested tips that can ensure outstanding customer service.Private and public SLAsSLA, also known as service level agreement, is a commitment made by the service provider with the consumer. It points out the service standards, responsibilities, first-response time, and a timeframe required to resolve the ticket’s issues.SLAs play ... Read More

Feed: Big Data Made Simple. Author: Daniel Munson. Today’s technology is advancing rapidly, and there is one clear trend these developments follow. The design philosophy that is leading the tech revolution is that of connectivity. The world around you is more connected and global than ever before. This has been a major boon to private citizens and corporate entities alike, but it brings with it new security concerns. The more people and businesses depend on technology, the more risk there is of their personal or business data falling into the wrong hands. Here’s what you need to know about keeping ... Read More

Feed: Featured Blog Posts - Data Science Central. Author: Avinash Udaykumar. Consistent asset health across many levels from cell sites to regions is critical to ensure uninterrupted operations for telecom operators. However, proactively identifying anomalous patterns like equipment malfunction remains a major challenge. Drawing on Subex’s deep implementation experience, this paper describes the chief steps necessary to deploy successful pattern detection solutions. It also examines some high impact use cases for pattern detection that have systematically delivered value for telecom carriers. High operational efficiency is an important differentiator for telecom operators establishing their brand reputation on consistency and service availability ... Read More

Feed: AWS Big Data Blog. The machine learning (ML) lifecycle consists of several key phases: data collection, data preparation, feature engineering, model training, model evaluation, and model deployment. The data preparation and feature engineering phases ensure an ML model is given high-quality data that is relevant to the model’s purpose. Because most raw datasets require multiple cleaning steps (such as addressing missing values and imbalanced data) and numerous data transformations to produce useful features ready for model training, these phases are often considered the most time-consuming in the ML lifecycle. Additionally, producing well-prepared training datasets has typically required extensive knowledge ... Read More