Data Analytics

Teradata Accelerates Sasol’s Digitization Journey With Cloud-Based Analytics Architecture

Teradata Accelerates Sasol’s Digitization Journey with Cloud-Based Analytics Architecture

Company wins prestigious Opti Award for innovative enterprise-ready analytical ecosystem Teradata (NYSE: TDC), the leading cloud-based data and analytics company, today announced that Sasol, a major international chemicals and energy company, is partnering with Teradata to create a robust analytical ecosystem that supports the company’s vision for creating a data-driven business strategy. Sasol – which operates in 33 countries with revenue topping $21 billion – began a digitization strategy in 2015 with the goal of enabling the organization to generate, manage and use data-driven insights faster. Sasol’s enterprise information management team worked with Teradata, via the South Africa-based BYTES Technology Group, to define a new data architecture with methods and processes that enable Sasol to construct an enterprise-wide analytics program that reduces costs and improves the customer experience.

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Live Data Management Platform Rapidly Aggregates and Unifies Varied Data Sources, Offers Tableau Server, Online, and Now Desktop Users Self-Service Analytics and Enables Real-Time Data Visualizations

MOUNTAIN VIEW, Calif. and AUSTIN, Texas – November 8, 2016 – Treasure Data, a leading cloud platform to make all data connected, current, and easily accessible, today announced full-stack integration with Tableau, adding new support for Tableau Desktop to expand upon its long time support for both Tableau Server and Tableau Online. By rapidly collecting and unifying data from various sources spread out across the enterprise and cloud, Treasure Data’s new Live Business Intelligence (BI) Connector for Tableau empowers business analytics teams to gain faster access and insights from their data sets.

Flytxt Launches Robo-X, The Artificial Intelligence Companion For Marketers

Flytxt launches Robo-X, the Artificial Intelligence companion for marketers

AI decisions throughout customer engagement cycle – from planning and execution to measurement and optimization Dubai: Flytxt today announced the launch of Robo-X, a first-of-its-kind Artificial Intelligence (AI) for Customer Engagement, which harnesses AI and Machine Learning to produce better marketing outcomes. Robo-X is an AI designed to work alongside marketers –¬ whether that’s identifying new upsell and cross-sell opportunities, discovering insightful patterns, advising on offers and campaigns or assessing performance and indicating areas for improvement. It uses Flytxt’s proprietary AI platform and machine learning algorithms to discover important relations between consumers, products, offers, channels and competitive environment and how they impact business outcomes.

Accelerite Shareinsights 2.0 Unifies Stack For True End-To-End Self-Service Big Data Analytics

Accelerite Shareinsights 2.0 Unifies Stack For True End-To-End Self-Service Big Data Analytics

SANTA CLARA, Calif. – December 12, 2017 — Accelerite, a provider of infrastructure software for digital transformation, today announced ShareInsights 2.0, an end-to-end, self-service big data analytics platform. Unlike other solutions, ShareInsights unifies the big data analytics stack, enabling data preparation (ETL), OLAP, visualization and collaboration — all via a single interface. that gives data analysts the ability to perform data preparation, analysis and visualization of millions of rows and terabytes of data in minutes ShareInsights also features Insight2Action, an automated process that directly connects insights with actions, making it a more valuable component of the data analysis lifecycle.

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Exabeam Announces New Threat Intelligence Service

LAS VEGAS – SPOTLIGHT 18 – Sept. 12, 2018 – Exabeam, the next-gen security management company, today announced Exabeam Threat Intelligence Service, a cloud-based offering that aggregates threat indicators from multiple online sources. The new service will be an integral part of the Exabeam Security Management Platform and available at no additional charge to customers with a current Exabeam subscription. Exabeam Threat Intelligence Service collects potential indicators of compromise (IoCs), including suspicious IP addresses, blacklisted IP addresses, known phishing URLs, and malicious file signatures. Machine algorithms are then applied to remove false positives and rank each indicator. To do this, the Exabeam Security Management Platform uses behavioral analytics techniques, similar to those used to assess users or devices, to baseline IoCs and gain a more relevant picture of the threats in the environment.

Alteryx Enhances The Analytic Journey With Visualytics

Alteryx Enhances The Analytic Journey With Visualytics

Irvine, Calif.—Aug. 28, 2018—Alteryx, Inc. (NYSE:AYX), revolutionizing business through data science and analytics, today announced the general availability of the newest version of the Alteryx analytics platform (2018.3). The release introduces new features that greatly enhance how users prepare, analyze, share and collaborate on data across the organization, now amplified with our newest innovation: Visualytics. Visualytics provides real-time, interactive visualizations across the Alteryx platform, enabling any data worker in an organization to easily visualize and understand their data throughout the entire analytics workflow, generating data-driven insights. Data analysts can now see their data at any point along the workflow to identify errors or outliers, make more informed decisions and streamline the analytics process. Inline Visualytics gives data scientists instant visual validation on the health of their analysis to maximize the effectiveness of business-critical models.

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DataRobot Announces Automated Time Series Solution that Allows Frontline Business People to Predict the Future

Boston, August 9, 2018 — DataRobot, the pioneering architects of automated machine learning, today announced the general availability of DataRobot Time Series. Following an extensive collaboration with more than 75 customers and world-class data scientists, this latest breakthrough completely automates sophisticated time series modeling. Finally, frontline business people can quickly build highly accurate forecasts for a diverse array of time-dependent prediction opportunities. Until now, handling time-dependency modeling required highly specialized expertise to even set up the problem correctly. Conventional modeling uses randomly selected records from a dataset to build and evaluate predictive models. For example, a representative sample of loan records and whether a customer defaulted. Each record is relatively similar.