UK researchers design machine learning method to predict battery health

governmentcomputing.com | April 07, 2020

A machine learning method has been designed by researchers from the Cambridge and Newcastle Universities that can predict health of batteries with 10 times more accuracy than the current industry standard.The University of Cambridge believes that the new method can help in developing safer and more reliable batteries used in electric vehicles and consumer electronics.The new method involves the sending of electrical pulses into batteries and measuring the response. The measurements are subsequently processed by a machine learning algorithm to predict the health and useful lifespan of the battery.The researchers used a machine learning model to discover specific characteristics in the electrical response that act as indications of battery aging. More than 20,000 experimental measurements are said to have been carried out to train the model to make the model learn how to distinguish important signals from irrelevant noise.

Spotlight

Tucked away in City Hall, a small team of data analyts has been unleashing a data revolution in New York City. Established under Mayor Michael Bloomberg, the Mayor’s Office of Data Analytics (MODA) combines and interrogates data from numerous different city sources to increase the efficiency and effectiveness of government operations and services. Big Data in the Big Apple provides a detailed account of the MODA model, its methods and achievements. It explains how MODA has helped to target the city’s resources at areas of greatest need, encourage collaboration between different departments and agencies, predict and prevent problems from occurring, and support economic development. The report argues that London should establish its own Mayor’s Office of Data Analytics to bring the same benefits to the British capital. Identifying the core principles and lessons from the experience of New York City, it outlines how the MODA model could be adapted to address the specific challenges facing London. Overall, Big Data in the Big Apple highlights how the methods established in New York represent one of the most powerful and effective models devised to date for harnessing data to improve city living.


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BIG DATA MANAGEMENT

Alteryx Announces New Cloud Capabilities that Empower Businesses to Deploy Analytics at Enterprise Scale

Alteryx | May 19, 2022

Alteryx, Inc., the Analytics Automation Company, today unveiled new advancements that empower enterprises to enable cloud analytics, democratize insights, and ensure data governance. Announced at the annual Alteryx user conference, Inspire, the groundbreaking enhancements simplify and modernize analytics with easy-to-use capabilities to deliver analytics for all. "Democratization of analytics is key to unlocking valuable insights in this rapidly changing business landscape, yet we have found fewer than 30 percent of knowledge workers have access to or are active users of analytics software beyond spreadsheets," said Dan Vesset, group vice president of Analytics and Information Management, IDC. "To become a truly data-driven enterprise, businesses need to leverage analytics solutions that support ubiquitous connectivity to data, rich governance, and powerful, intuitive decision support capabilities." Ubiquitous Connectivity Enables Modern Cloud Analytics Today, data-driven enterprises require analytics automation platforms and data architectures that span cloud, on-premises, and hybrid environments. Organizations are increasingly deploying modern data architectures built on cloud data warehouses and data lakehouses, while also supporting SaaS applications and analytics. Alteryx delivers on these needs by offering intelligent data transformation and insights in the cloud at scale. Bolstered by its recent acquisition of Trifacta, Alteryx offers enhanced integrations with leading cloud data warehouses including Databricks, Snowflake, and Google BigQuery. The integrations support high-performance native pushdown capabilities, shortening the time to derive insights from big data sets from hours to minutes. "With unmatched scale and flexibility, cloud analytics is key for the future of digital transformation. Coupled with our advanced capabilities in analytics automation and governance, Alteryx leads the way in empowering organizations to easily democratize data for every person, at every skill level. "Our latest innovations enable businesses to become data-driven and overcome potential obstacles including data silos and talent scarcity." Suresh Vittal, chief product officer at Alteryx New Capabilities Deliver Insights with Ease Businesses can further drive analytics automation for all with new, easy-to-use capabilities across the full Alteryx product portfolio. New ease of use capabilities include: Alteryx Designer has been updated for a modern look and feel with new tools, layout icons, and fonts. Alteryx Intelligence Suite includes capabilities for Text Mining and Computer Vision including barcode reader tool, part of speech tool, and key value pair tool. These intelligent tools allow any users to easily analyze unstructured data. Alteryx Auto Insights now comes seamlessly integrated with Designer Desktop and Server. Users can now automatically connect, configure and schedule Auto Insights from their workflows to gain AI-driven insights from their data. Alteryx Machine Learning offers substantial enhancements to predictive Time Series Modeling, including new functionality that allows for trending, seasonality, and increased performance which enables any business user to build machine learning models. Alteryx is starting Early Access for its Metric Store capability. The Metric store will allow enterprises to easily define standard key performance indicators that can be reused by anyone in the organization to rapidly, consistently, and accurately derive insights. Governance Advancements Enable Enterprise Scale Analytics As businesses democratize analytic automation, it is essential to support robust governance practices to protect data integrity. New Alteryx governance capabilities include: Designer Cloud powered by Trifacta, which brings together Alteryx Designer's ease of use with the Trifacta cloud-native multi-tenant architecture, adds SSH tunneling capabilities to enhance security in the cloud. Alteryx now also officially supports persistent and non-persistent Virtual Desktop Infrastructure (VDI) deployments enabling enterprises to easily manage Alteryx in large scale virtualized environments. In all, these latest developments and enhanced cloud connectivity enable Alteryx customers to embrace analytics automation and derive insights across the organization. Alteryx will dive deeper into each of these topics, as well as customer stories, trends, and more at the Inspire 2022 conference. Watch sessions on-demand at alteryx.com/inspire. About Alteryx Alteryx, the Analytics Automation company, is focused on enabling every person to transform data into a breakthrough. Alteryx unifies analytics, data science and business process automation in one, end-to-end platform to accelerate digital transformation and shape the future of analytics automation. Organizations of all sizes, all over the world, rely on Alteryx to deliver high-impact business outcomes and the rapid upskilling of their modern workforce.

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BIG DATA MANAGEMENT

Phocas Software selected as preferred data analytics technology by ADS Solutions

Phocas Software | March 21, 2022

A new partnership between Phocas Software and ADS Solutions will help small- to mid-sized businesses in the wholesale distribution and light manufacturing industries use their business data to improve reporting, insights and decision making. ADS Solutions, creator of cloud-based Accolent ERP, has selected Phocas as its preferred data analytics platform to complement the ADS Solutions application. Together, Phocas and ADS Solutions will create a list of standardized reporting and dashboards for Accolent ERP customers by industry with a goal of delivering a more efficient reporting solution and allowing users to quickly and easily monitor key performance indicators (KPIs). “As cloud-based solution providers with thousands of users in wholesale and manufacturing, Phocas and ADS Solutions understand the value of delivering technology that is intuitive, readily available and optimized for specific industries,” said Jay Deubler, president of Phocas U.S. “Out-of-the-box, Phocas is primed to help Accolent ERP customers with reporting and dashboards they need to eliminate guesswork and be more strategic with critical business decisions. We have purposely built Phocas to integrate seamlessly with solutions like Accolent ERP and encourage quick and broad adoption because of its simplicity and familiarity.” “Accolent ERP customers need an intuitive data analytics and reporting solution that Phocas Software can provide. With only a few clicks, Phocas will provide Accolent ERP customers with access to easy-to-understand, actionable business intelligence, allowing them to fully capitalize on the value of their information.” Ian Pereira, CEO of ADS Solutions Phocas has more than 30,000 daily users, and is built with KPIs and metrics that are specific to roles and industries of ADS Solutions’ customers. Phocas will provide ADS Solutions with extensive sales and technical training about its base business intelligence platform, Financial Statements solution and Budgeting and Forecasting workflows. ADS Solutions’ customers will also have access to Phocas vast online training and support tools, including Phocas Academy and Phocas User Group Forum. About Phocas Software Phocas is a cloud-based, SaaS company specializing in data analytics for the manufacturing, distribution, retail industries. The software incorporates sector knowledge to consolidate essential business data from common ERP, CRM, and AP/AR systems to make it simple to access companywide insights and financial performance through historical and predictive analysis. A core philosophy at Phocas is to make software intuitive so users of all skill levels can track and report on essential KPIs that are specific to their roles and industries. Phocas comes with out-of-the-box metrics, powerful interactive dashboards and broad functionality to provide immediate benefits and adoption. Users can also customize the software to meet their unique analytics and reporting needs. About ADS Solutions ADS Solutions is a leader in providing powerful, intuitive, and easy-to-use Cloud-based ERP software to wholesale distributors, light manufacturers and services businesses. ADS Solutions’ Accolent ERP software delivers fully integrated, end-to-end functionality for sales, CRM, order management, inventory control, warehouse management, fulfillment, purchasing, eCommerce and GAAP financial reporting capabilities. Accolent ERP is optimized for the wholesale distributors, light manufacturers and services businesses, across a broad range of vertical industries.

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DATA SCIENCE

Introducing Neo4j Graph Data Science as a Service

Neo4j | April 13, 2022

Neo4j®, the world's leading graph data platform, announced Neo4j Graph Data Science, the company's comprehensive graph analytics workspace built for data scientists, is now available with new and enhanced capabilities, and as a fully managed cloud service called AuraDS. AI and machine learning (ML) have propelled the use of predictive data architectures and their application across a broad range of use cases like recommendation engines, fraud detection, and customer 360 scenarios. The accuracy of these models is highly correlated to the completeness of context. Neo4j Graph Data Science is designed to make it easy for data scientists to achieve greater predictive accuracy with comprehensive graph analysis techniques. Users can improve models through a library of graph algorithms, ML pipelines, and data science methods. Neo4j Graph Data Science has been widely adopted and is trusted to perform at scale, easily handling hundreds of billions of nodes and relationships. "Neo4j Graph Data Science offerings help developers offer better predictions and stronger recommendation engines to business users. Customers can now deploy Graph Data Science on Google Cloud's trusted, global infrastructure, gaining the ability to seamlessly scale based on business needs, and bringing their data closer to BigQuery and Google Cloud's capability in AI, ML, and analytics. Ritika Suri, Director, Technology Partnerships at Google "More software developers are looking to data science for ways to offer better predictions and stronger recommendation engines to users. Google Cloud and Neo4j Graph Data Science products help software developers and data scientists who are building the world's next set of intelligent applications by leveraging the power of graph algorithms to bring context to data and improve their models," said Suri. Neo4j Graph Data Science makes it easy for data scientists to work within their existing data pipeline of tools across their ecosystem. Data scientists can use Neo4j Graph Data Science on-premises, and now as a fully managed SaaS solution via Neo4j AuraDS. According to Zack Gow, CTO of Orita, Neo4j Graph Data Science has enabled his team to be more responsive to customer needs. "Scale is always top of mind for us because we're processing data that comes from our customers. We never know just how big a customer's data set will be and we chose Neo4j because we knew it could handle the scaling of an order of magnitude more than what we were expecting," Gow said. "Even in the early days, when we were trying out a bunch of tools, Neo4j worked for us immediately. Some of the tools we looked at didn't work at all. Neo4j Graph Data Science got our data into a graph so we could start doing the data science part quickly. As a start up, we don't have time to waste on tools that are cumbersome." Matthew Bernardini, CEO of Zenapse, shared the impact of Neo4j Graph Data Science on his business. "We chose Neo4j Graph Data Science on AuraDS because it is a completely managed, cloud-based infrastructure combined with an elegant and user-friendly set of tools and extensive library of production-ready data science algorithms that gives us confidence in our platform and allows us to focus on our data and application development," said Bernardini. "Neo4j Graph Data Science makes it easy to quantify the relationships and similarities that exist in the digital world and to surface new insights about these connected relationships." Neo4j AuraDS: Graph Data Science on Google Cloud Platform Neo4j AuraDS is the power of Graph Data Science available as a fully managed service. It includes access to over 65 graph algorithms in a single workspace so data scientists can experiment faster. In-graph ML models and the native Python client help increase productivity and simplify workflows. Neo4j AuraDS is available first on Google Cloud's secure, global, and highly performant structure, and can be paid for with existing Google Cloud commitments or with a credit card. In addition to the Graph Data Science core functionality, AuraDS customers benefit from: Simple, powerful workflow: A drag-and-drop UI to model and import data into a graph. Scale up and down: Manage access to high compute hardware on-demand as needs change. Automated operations: Workloads are monitored, patched, and backed up behind the scenes without any user action. MLOps support: Persist, publish, and restore models without interruptions from restarts. Predictable cost: Manage costs with pay-as-you-go pricing and the option of pausing unused instances. One-click backup: Take a snapshot of instances, models, and in-memory graphs in one click. For guidance and reference architectures on how to get started using Neo4j AuraDS with VertexAI, see Use graphs for smarter AI with Neo4j and Google Cloud Vertex AI. More About Neo4j Graph Data Science and AuraDS To learn more about Neo4j Graph Data Science as a service, AuraDS, read this blog post or tune in to an upcoming webinar, "What's New in Graph Data Science: Faster and Easier Than Before," on Tuesday, April 26, 2022. About Neo4j Neo4j is the world's leading graph data platform. We help organizations – including Comcast, ICIJ, NASA, UBS, and Volvo Cars – capture the rich context of the real world that exists in their data to solve challenges of any size and scale. Our customers transform their industries by curbing financial fraud and cybercrime, optimizing global networks, accelerating breakthrough research, and providing better recommendations.

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DATA ARCHITECTURE

Databricks Launches Data Lakehouse for Retail and Consumer Goods Customers

Databricks | January 14, 2022

Databricks, the Data and AI company and pioneer of the data lakehouse architecture, today announced the Databricks Lakehouse for Retail, the company's first industry-specific data lakehouse for retailers and consumer goods (CG) customers. With Databricks' Lakehouse for Retail, data teams are enabled with a centralized data and AI platform that is tailored to help solve the most critical data challenges that retailers, partners, and their suppliers are facing. Early adopters of Databricks' Lakehouse for Retail include industry-leading customers and partners like Walgreens, Columbia, H&M Group, Reckitt, Restaurant Brands International, 84.51°(a subsidiary of Kroger Co.), Co-Op Food, Gousto, Acosta and more. "As the retail and healthcare industries continue to undergo transformative change, Walgreens has embraced a modern, collaborative data platform that provides a competitive edge to the business and, most importantly, equips our pharmacists and technicians with timely, accurate patient insights for better healthcare outcomes," said Luigi Guadagno, Vice President, Pharmacy and HealthCare Platform Technology at Walgreens. "With hundreds of millions of prescriptions processed by Walgreens each year, Databricks' Lakehouse for Retail allows us to unify all of this data and store it in one place for a full range of analytics and ML workloads. By eliminating complex and costly legacy data silos, we've enabled cross-domain collaboration with an intelligent, unified data platform that gives us the flexibility to adapt, scale and better serve our customers and patients." "Databricks has always innovated on behalf of our customers and the vision of lakehouse helps solve many of the challenges retail organizations have told us they're facing," said Ali Ghodsi, CEO and Co-Founder at Databricks. "This is an important milestone on our journey to help organizations operate in real-time, deliver more accurate analysis, and leverage all of their customer data to uncover valuable insights. Lakehouse for Retail will empower data-driven collaboration and sharing across businesses and partners in the retail industry." Databricks' Lakehouse for Retail delivers an open, flexible data platform, data collaboration and sharing, and a collection of powerful tools and partners for the retail and consumer goods industries. Designed to jumpstart the analytics process, new Lakehouse for Retail Solution Accelerators offer a blueprint of data analytics and machine learning use cases and best practices to save weeks or months of development time for an organization's data engineers and data scientists. Popular solution accelerators for Databricks' Lakehouse for Retail customers include: Real-time Streaming Data Ingestion: Power real-time decisions critical to winning in omnichannel retail with point-of-sale, mobile application, inventory and fulfillment data. Demand forecasting and time-series forecasting: Generate more accurate forecasts in less time with fine-grained demand forecasting to better predict demand for all items and stores. ML-powered recommendation engines: Specific recommendations models for every stage of the buyer journey - including neural network, collaborative filtering, content-based recommendations and more - enable retailers to create a more personalized customer experience. Customer Lifetime Value: Examine customer attrition, better predict behaviors of churn, and segment consumers by lifetime and value with a collection of customer analytics accelerators to help improve decisions on product development and personalized promotions. Additionally, industry-leading Databricks partners like Deloitte and Tredence are driving lakehouse vision and value by delivering pre-built analytics solutions on the lakehouse platform that address real-time customer use cases. Tailor-made for the retail industry, featured partner solutions and platforms include: Deloitte's Trellis solution accelerator for the retail industry is one of many examples of how Deloitte and client partners are adopting the Databricks Lakehouse architecture construct and platform to deliver end-to-end data and AI/ML capabilities in a simple, holistic, and cost-effective way. Trellis provides capabilities that solve retail clients' complex challenges around forecasting, replenishment, procurement, pricing, and promotion services. Deloitte has leveraged their deep industry and client expertise to build an integrated, secured, and multi-cloud ready "as-a-service" solution accelerator on top of Databricks' Lakehouse platform that can be rapidly customized as appropriate based on client's unique needs. Trellis has proven to be a game-changer for our joint clients as it allows them to focus on the critical shifts occurring both on the demand and supply side with the ability to assess recommendations, associated impact, and insights in real-time that result in significant improvement to both topline and bottom line numbers. Tredence will meet the explosive enterprise Data, AI & ML demand and deliver real-time transformative industry value for their business by delivering solutions for Lakehouse for Retail. The partnership first launched the On-Shelf Availability Solution (OSA) accelerator in August 2021, combining Databricks' data processing capability and Tredence's AI/ML expertise to enable Retail, CPG & Manufacturers to solve their trillion dollar out-of-stock challenge. Now with Lakehouse for Retail, Tredence and Databricks will jointly expand the portfolio of industry solutions to address other customer challenges and drive global scale together. About Databricks Databricks is the data and AI company. More than 5,000 organizations worldwide — including Comcast, Condé Nast, H&M, and over 40% of the Fortune 500 — rely on the Databricks Lakehouse Platform to unify their data, analytics and AI. Databricks is headquartered in San Francisco, with offices around the globe. Founded by the original creators of Apache Spark™, Delta Lake and MLflow, Databricks is on a mission to help data teams solve the world's toughest problems.

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Spotlight

Tucked away in City Hall, a small team of data analyts has been unleashing a data revolution in New York City. Established under Mayor Michael Bloomberg, the Mayor’s Office of Data Analytics (MODA) combines and interrogates data from numerous different city sources to increase the efficiency and effectiveness of government operations and services. Big Data in the Big Apple provides a detailed account of the MODA model, its methods and achievements. It explains how MODA has helped to target the city’s resources at areas of greatest need, encourage collaboration between different departments and agencies, predict and prevent problems from occurring, and support economic development. The report argues that London should establish its own Mayor’s Office of Data Analytics to bring the same benefits to the British capital. Identifying the core principles and lessons from the experience of New York City, it outlines how the MODA model could be adapted to address the specific challenges facing London. Overall, Big Data in the Big Apple highlights how the methods established in New York represent one of the most powerful and effective models devised to date for harnessing data to improve city living.

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