Alteryx is a Leading platform for data analytics with Self-service data analytics software that enables deeper insights from data, faster than ever before
See More: https://www.simpleanalyticsinc.com/
This document discusses the Alteryx tool, a drag-and-drop data analytics platform. It provides an overview of what Alteryx is, how it can be used for tasks like data cleaning and predictive analysis, and why it can save time over traditional coding methods. Specific features are highlighted, like accessing over 80 data sources, 260+ tools for analytics, and exporting reports in various formats. In conclusion, Alteryx is suitable for both data scientists and less technical users due to its code-free interface and ability to perform sophisticated analysis quickly.
The Alteryx Designer solves this by delivering an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks typical of traditional approaches! The Alteryx Designer empowers data analysts by combining data blending, predictive analytics, spatial analytics, and reporting, visualization and analytic apps into one workflow.
Here are some of the things our Data Analytics team can doLoren Moss
Using tools like Alteryx, AWS Quicksight, and methods such as RegEx, JSON, Python, SQL and SPARQL we can help extract the knowledge hidden in your data. www.unidodigital.com
Top 10 Data analytics tools to look for in 2021Mobcoder
This write-up has surrounded the top 10 tools used by data analysts, architects, scientists, and other professionals. Each tool has some specific feature that makes it an ideal fit for a specific task. So choose wisely depending on your business need, type of data, the volume of information, experience in analytical thinking.
Leveraging cloud database connectors to automate analytics in alteryxGrazitti Interactive
This webinar discusses leveraging cloud database connectors to automate analytics in Alteryx. It introduces Grazitti Interactive, an Alteryx partner that develops connectors. The webinar covers the growth of cloud databases, how Alteryx helps analyze database data, challenges integrating databases into Alteryx, an overview of Alteryx connectors, and how Grazitti created a custom Azure Analysis Services connector for a customer.
Embrace The Latest Tableau Innovations Right From Day One
Want to get the most out of the latest version of Tableau? Curious to know what are the new innovations? Well, it’s time to upgrade your Tableau deployment!
- The new innovations available in the latest Tableau release (data prep & data model, visualization, IT governance)
- Tableau upgrade methodology
- How to relieve the pain of testing thanks to Kinesis-CI.
Our partner: https://systechusa.com/
Tableau is a business intelligence tool that helps people see and understand data through visualizations. The presentation covered an overview of Tableau, why it is useful for organizations, and provided a live demonstration of its key capabilities like sourcing and cleaning data, visualizing data in Tableau Desktop, and deploying visualizations on Tableau Server.
Experience Tableau's hands-on training through instructor-led, live and on-demand courses. Our Instructors deliver what are the qualities required to become proficient in Tableau to all the individuals
This document discusses the Alteryx tool, a drag-and-drop data analytics platform. It provides an overview of what Alteryx is, how it can be used for tasks like data cleaning and predictive analysis, and why it can save time over traditional coding methods. Specific features are highlighted, like accessing over 80 data sources, 260+ tools for analytics, and exporting reports in various formats. In conclusion, Alteryx is suitable for both data scientists and less technical users due to its code-free interface and ability to perform sophisticated analysis quickly.
The Alteryx Designer solves this by delivering an intuitive workflow for data blending and advanced analytics that leads to deeper insights in hours, not the weeks typical of traditional approaches! The Alteryx Designer empowers data analysts by combining data blending, predictive analytics, spatial analytics, and reporting, visualization and analytic apps into one workflow.
Here are some of the things our Data Analytics team can doLoren Moss
Using tools like Alteryx, AWS Quicksight, and methods such as RegEx, JSON, Python, SQL and SPARQL we can help extract the knowledge hidden in your data. www.unidodigital.com
Top 10 Data analytics tools to look for in 2021Mobcoder
This write-up has surrounded the top 10 tools used by data analysts, architects, scientists, and other professionals. Each tool has some specific feature that makes it an ideal fit for a specific task. So choose wisely depending on your business need, type of data, the volume of information, experience in analytical thinking.
Leveraging cloud database connectors to automate analytics in alteryxGrazitti Interactive
This webinar discusses leveraging cloud database connectors to automate analytics in Alteryx. It introduces Grazitti Interactive, an Alteryx partner that develops connectors. The webinar covers the growth of cloud databases, how Alteryx helps analyze database data, challenges integrating databases into Alteryx, an overview of Alteryx connectors, and how Grazitti created a custom Azure Analysis Services connector for a customer.
Embrace The Latest Tableau Innovations Right From Day One
Want to get the most out of the latest version of Tableau? Curious to know what are the new innovations? Well, it’s time to upgrade your Tableau deployment!
- The new innovations available in the latest Tableau release (data prep & data model, visualization, IT governance)
- Tableau upgrade methodology
- How to relieve the pain of testing thanks to Kinesis-CI.
Our partner: https://systechusa.com/
Tableau is a business intelligence tool that helps people see and understand data through visualizations. The presentation covered an overview of Tableau, why it is useful for organizations, and provided a live demonstration of its key capabilities like sourcing and cleaning data, visualizing data in Tableau Desktop, and deploying visualizations on Tableau Server.
Experience Tableau's hands-on training through instructor-led, live and on-demand courses. Our Instructors deliver what are the qualities required to become proficient in Tableau to all the individuals
This document provides an overview of Einstein Analytics, including:
1. Einstein Analytics is a cloud-based business intelligence platform that allows users to interactively explore and gain insights from their data through applications, visualizations, and self-service AI capabilities.
2. It can connect to various data sources like Salesforce objects, file uploads, and external sources via connectors. Dataflows and recipes are used to combine, transform, and prepare this data for analysis in datasets.
3. Lenses and dashboards are then used to interactively analyze and gain knowledge from the datasets, with filters allowing customization. Security controls access at the sharing and field level.
Big Data Berlin v8.0 Stream Processing with Apache Apex Apache Apex
This document discusses Apache Apex, an open source stream processing framework. It provides an overview of stream data processing and common use cases. It then describes key Apache Apex capabilities like in-memory distributed processing, scalability, fault tolerance, and state management. The document also highlights several customer use cases from companies like PubMatic, GE, and Silver Spring Networks that use Apache Apex for real-time analytics on data from sources like IoT sensors, ad networks, and smart grids.
Doing data visualizations with tableauRay Schwartz
This document summarizes a presentation on using Tableau for data visualization. It introduces the main Tableau products: Tableau Desktop for creating visualizations, Tableau Server for enterprise deployments, Tableau Online for cloud hosting, and Tableau Public for freely sharing visualizations online. It demonstrates how to connect data and create workbooks and dashboards in Tableau Desktop. It also discusses the Tableau APIs for extracting data, publishing to Server, and integrating visualizations into other web applications.
Doing data visualizations with tableauRay Schwartz
This document provides an overview of Tableau, a data visualization software. It describes the main Tableau products: Tableau Desktop for individuals, Tableau Server for enterprises, Tableau Online for cloud hosting, and Tableau Public for free sharing. It demonstrates how to connect data and create workbooks and dashboards in Tableau. It also discusses the Tableau SDK for integrating visualizations and the Tableau JavaScript API.
An in-depth virtual session on Einstein Analytics on the Belgian Salesforce Administrators user group. What is Einstein Analytics, how does it compare to standard Salesforce Reports & Dashboards, an in-depth demo and how do you quickstart your knowledge on EA.
Optier presentation for open analytics eventOpen Analytics
1. The document discusses how traditional analytics processes are flawed and inefficient due to the way application data is stored.
2. It introduces OpTier's patented technology, which can collect data from applications in real-time as transactions are processed, without changing the applications. This data is tagged and put into context to enable useful real-time analytics.
3. OpTier claims its solution can significantly reduce the time and money spent on analytics projects by capturing transactional data in real-time and near-real time using proven technology, decreasing reliance on ETL tools, and leveraging the power and economics of Cassandra databases.
Tableau is a business intelligence tool that helps people see and understand data. It allows users to source and clean data, visualize it in Tableau Desktop, and gain insights. The presentation then demonstrated Tableau's capabilities by showcasing how to prepare data in Tableau Prep, visualize it in Tableau Desktop, and deploy the dashboard or report to Tableau Server for sharing and governance.
Alteryx is a data blending and advanced analytics software company. It offers two main products: Alteryx Designer, which allows business analysts to create repeatable workflows for accessing, blending, and analyzing data; and Alteryx Server, which provides a scalable server-based solution for sharing and running analytic applications in a web-based environment. The Alteryx platform uses a drag-and-drop interface to blend data sources, perform advanced analytics, and share insights. It can be deployed both locally with Designer or in a server configuration with Designer, Server, and Gallery components.
This document discusses realizing business value from open source data and intelligence. It provides an example of using sentiment analysis on 500,000 Enron emails to prioritize analysis. Key findings include highlighting 801 weeks for manual review based on negative sentiment shifts. Lessons learned are that sentiment analysis can drastically reduce analysis timelines and the technique has multiple potential uses for intelligence analysis, e-discovery, brand management, and social media analysis.
This document provides an introduction to Insights for ArcGIS, a new spatial analytics tool. It discusses how Insights allows users to explore, analyze, visualize and iterate on data through drag and drop functionality. Insights connects to various data sources and allows users to record workflows, share results, and tell stories through embedded visualizations and analysis. The document outlines how Insights can provide value to different user types, including GIS professionals, through fast, powerful data discovery and the ability to share analysis results.
This document provides an overview of Microsoft R and its capabilities for advanced analytics. It discusses how Microsoft R can enable businesses to analyze large volumes of data across multiple environments including locally, on Azure, and with SQL Server and HDInsight. The presentation includes a demonstration of R used with SQL Server, HDInsight, Azure Machine Learning, and Power BI. It highlights how Microsoft R provides a unified platform for data science and analytics that allows users to write code once and deploy models anywhere.
Azure Data Platform Services
HDInsight Clusters in Azure
Data Storage: Apache Hive, Apache Hbase, Azure Data Catalog
Data Transformations: Apache Storm, Apache Spark, Azure Data Factory
Healthcare / Life Sciences Use Cases
The challenges of Analytical Data Management in R&DLaura Berry
Presented at the Global Pharma R&D Informatics Congress. To find out more, visit:
www.global-engage.com
Analytical data is at the heart of pharmaceutical research, yet many organisations struggle with the variety of different formats, instrument vendors, and search and retrieval of data. In this presentation, Hans de Bie from ACD/Labs discusses automated capture, exchange formats, integrity, and next generation management systems.
Skill up in machine learning using Azure MLMostafa
Data drives decisions and actions. Machine learning uses data to build models that can predict unknown data. The machine learning process involves getting data, preparing it by extracting features, training a model on known data and labels, and evaluating the model's performance on predicting labels of unknown data. These trained models can then be deployed as web services to power applications.
microsoft r server for distributed computingBAINIDA
The document introduces Microsoft R Server and Microsoft R Open. It discusses that R is a popular open source programming language and platform for statistics, analytics, and data science. Microsoft R Server allows for distributed computing on big data using R and brings enterprise-grade support and capabilities to the open source R platform. It can perform analytics both in-database using SQL Server and in Hadoop environments without moving data.
Why do the majority of Data Science projects never make it to production?Itai Yaffe
María de la Fuente (Solutions Architect Manager for IMEA) @ Databricks
While most companies understand the value creation of leveraging data and are taking on board an AI strategy, only 13% of the data science projects make it to production successfully.
Besides the well-known skills gap in the market, we need to level up our end-to-end approach and cover all aspects involved when working with AI.
In this session, we will discuss the main obstacles to overcome and how we can avoid the major pitfalls to ensure our data science journey becomes successful.
Building a MLOps Platform Around MLflow to Enable Model Productionalization i...Databricks
Getting machine learning models to production is notoriously difficult: it involves multiple teams (data scientists, data and machine learning engineers, operations, …), who often does not speak to each other very well; the model can be trained in one environment but then productionalized in completely different environment; it is not just about the code, but also about the data (features) and the model itself… At DataSentics, as a machine learning and cloud engineering studio, we see this struggle firsthand – on our internal projects and client’s projects as well.
Empowering Real Time Patient Care Through Spark StreamingDatabricks
Takeda’s Plasma Derived Therapies (PDT) business unit has recently embarked on a project to use Spark Streaming on Databricks to empower how they deliver value to their Plasma Donation centers. As patients come in and interface without clinics, we store and track all of the patient interactions in real time and deliver outputs and results based on said interactions. The current problem with our existing architecture is that it is very expensive to maintain and has an unsustainable number of failure points. Spark Streaming is essential for allowing this use case because it allows for a more robust ETL pipeline. With Spark Streaming, we are able to replace our existing ETL processes (that are based on Lamdbas, step functions, triggered jobs, etc) into a purely stream driven architecture.
Data is brought into our s3 raw layer as a large set of CSV files through AWS DMS and Informatica IICS as these services bring data from on-prem systems into our cloud layer. We have a stream currently running which takes these raw files up and merges them into Delta tables established in the bronze/stage layer. We are using AWS Glue as the metadata provider for all of these operations. From the stage layer, we have another set of streams using the stage Delta tables as their source, which transform and conduct stream to stream lookups before writing the enriched records into RDS (silver/prod layer). Once the data has been merged into RDS we have a DMS task which lifts the data back into S3 as CSV files. We have a small intermediary stream which merge these CSV files into corresponding delta tables, from which we have our gold/analytic streams. The on-prem systems are able to speak to the silver layer and allow for the near real-time latency that our patient care centers require.
This presentation describes the philosophy, the features and the future plans that we have about the Parashar21 platform of Indian Astrology
_________________________________________________________________
The new Windows Live Messenger. You don’t want to miss this.
http://www.microsoft.com/india/windows/windowslive/messenger.aspx
This document provides an overview of the Alteryx self-service data analytics platform. It describes Alteryx as a platform that combines data preparation, blending, and predictive, statistical and spatial analytics in an intuitive interface. It then discusses the different types of users of Alteryx, including data analysts, BI developers, and DBAs. Finally, it promotes trying Alteryx for free and provides a demonstration of its data preparation, blending, statistical analysis and spatial analysis capabilities using Pokémon Go datasets.
Alteryx Tutorial Step by Step Guide for BeginnersVishnuGone
Alteryx is perhaps the most well known BI stages that allows association to address business questions quickly and capably. The stage can be used as a critical construction block in an advanced change or computerization drive. Alteryx is utilized for information purifying, which has confounded characteristics between two data sources, NULL qualities, letters, or crude information and zeros in the information. Alteryx can likewise be utilized to investigate business open doors further develop independent direction. Alteryx permits us to rapidly get to, control, dissect, and yield information.
This document provides an overview of Einstein Analytics, including:
1. Einstein Analytics is a cloud-based business intelligence platform that allows users to interactively explore and gain insights from their data through applications, visualizations, and self-service AI capabilities.
2. It can connect to various data sources like Salesforce objects, file uploads, and external sources via connectors. Dataflows and recipes are used to combine, transform, and prepare this data for analysis in datasets.
3. Lenses and dashboards are then used to interactively analyze and gain knowledge from the datasets, with filters allowing customization. Security controls access at the sharing and field level.
Big Data Berlin v8.0 Stream Processing with Apache Apex Apache Apex
This document discusses Apache Apex, an open source stream processing framework. It provides an overview of stream data processing and common use cases. It then describes key Apache Apex capabilities like in-memory distributed processing, scalability, fault tolerance, and state management. The document also highlights several customer use cases from companies like PubMatic, GE, and Silver Spring Networks that use Apache Apex for real-time analytics on data from sources like IoT sensors, ad networks, and smart grids.
Doing data visualizations with tableauRay Schwartz
This document summarizes a presentation on using Tableau for data visualization. It introduces the main Tableau products: Tableau Desktop for creating visualizations, Tableau Server for enterprise deployments, Tableau Online for cloud hosting, and Tableau Public for freely sharing visualizations online. It demonstrates how to connect data and create workbooks and dashboards in Tableau Desktop. It also discusses the Tableau APIs for extracting data, publishing to Server, and integrating visualizations into other web applications.
Doing data visualizations with tableauRay Schwartz
This document provides an overview of Tableau, a data visualization software. It describes the main Tableau products: Tableau Desktop for individuals, Tableau Server for enterprises, Tableau Online for cloud hosting, and Tableau Public for free sharing. It demonstrates how to connect data and create workbooks and dashboards in Tableau. It also discusses the Tableau SDK for integrating visualizations and the Tableau JavaScript API.
An in-depth virtual session on Einstein Analytics on the Belgian Salesforce Administrators user group. What is Einstein Analytics, how does it compare to standard Salesforce Reports & Dashboards, an in-depth demo and how do you quickstart your knowledge on EA.
Optier presentation for open analytics eventOpen Analytics
1. The document discusses how traditional analytics processes are flawed and inefficient due to the way application data is stored.
2. It introduces OpTier's patented technology, which can collect data from applications in real-time as transactions are processed, without changing the applications. This data is tagged and put into context to enable useful real-time analytics.
3. OpTier claims its solution can significantly reduce the time and money spent on analytics projects by capturing transactional data in real-time and near-real time using proven technology, decreasing reliance on ETL tools, and leveraging the power and economics of Cassandra databases.
Tableau is a business intelligence tool that helps people see and understand data. It allows users to source and clean data, visualize it in Tableau Desktop, and gain insights. The presentation then demonstrated Tableau's capabilities by showcasing how to prepare data in Tableau Prep, visualize it in Tableau Desktop, and deploy the dashboard or report to Tableau Server for sharing and governance.
Alteryx is a data blending and advanced analytics software company. It offers two main products: Alteryx Designer, which allows business analysts to create repeatable workflows for accessing, blending, and analyzing data; and Alteryx Server, which provides a scalable server-based solution for sharing and running analytic applications in a web-based environment. The Alteryx platform uses a drag-and-drop interface to blend data sources, perform advanced analytics, and share insights. It can be deployed both locally with Designer or in a server configuration with Designer, Server, and Gallery components.
This document discusses realizing business value from open source data and intelligence. It provides an example of using sentiment analysis on 500,000 Enron emails to prioritize analysis. Key findings include highlighting 801 weeks for manual review based on negative sentiment shifts. Lessons learned are that sentiment analysis can drastically reduce analysis timelines and the technique has multiple potential uses for intelligence analysis, e-discovery, brand management, and social media analysis.
This document provides an introduction to Insights for ArcGIS, a new spatial analytics tool. It discusses how Insights allows users to explore, analyze, visualize and iterate on data through drag and drop functionality. Insights connects to various data sources and allows users to record workflows, share results, and tell stories through embedded visualizations and analysis. The document outlines how Insights can provide value to different user types, including GIS professionals, through fast, powerful data discovery and the ability to share analysis results.
This document provides an overview of Microsoft R and its capabilities for advanced analytics. It discusses how Microsoft R can enable businesses to analyze large volumes of data across multiple environments including locally, on Azure, and with SQL Server and HDInsight. The presentation includes a demonstration of R used with SQL Server, HDInsight, Azure Machine Learning, and Power BI. It highlights how Microsoft R provides a unified platform for data science and analytics that allows users to write code once and deploy models anywhere.
Azure Data Platform Services
HDInsight Clusters in Azure
Data Storage: Apache Hive, Apache Hbase, Azure Data Catalog
Data Transformations: Apache Storm, Apache Spark, Azure Data Factory
Healthcare / Life Sciences Use Cases
The challenges of Analytical Data Management in R&DLaura Berry
Presented at the Global Pharma R&D Informatics Congress. To find out more, visit:
www.global-engage.com
Analytical data is at the heart of pharmaceutical research, yet many organisations struggle with the variety of different formats, instrument vendors, and search and retrieval of data. In this presentation, Hans de Bie from ACD/Labs discusses automated capture, exchange formats, integrity, and next generation management systems.
Skill up in machine learning using Azure MLMostafa
Data drives decisions and actions. Machine learning uses data to build models that can predict unknown data. The machine learning process involves getting data, preparing it by extracting features, training a model on known data and labels, and evaluating the model's performance on predicting labels of unknown data. These trained models can then be deployed as web services to power applications.
microsoft r server for distributed computingBAINIDA
The document introduces Microsoft R Server and Microsoft R Open. It discusses that R is a popular open source programming language and platform for statistics, analytics, and data science. Microsoft R Server allows for distributed computing on big data using R and brings enterprise-grade support and capabilities to the open source R platform. It can perform analytics both in-database using SQL Server and in Hadoop environments without moving data.
Why do the majority of Data Science projects never make it to production?Itai Yaffe
María de la Fuente (Solutions Architect Manager for IMEA) @ Databricks
While most companies understand the value creation of leveraging data and are taking on board an AI strategy, only 13% of the data science projects make it to production successfully.
Besides the well-known skills gap in the market, we need to level up our end-to-end approach and cover all aspects involved when working with AI.
In this session, we will discuss the main obstacles to overcome and how we can avoid the major pitfalls to ensure our data science journey becomes successful.
Building a MLOps Platform Around MLflow to Enable Model Productionalization i...Databricks
Getting machine learning models to production is notoriously difficult: it involves multiple teams (data scientists, data and machine learning engineers, operations, …), who often does not speak to each other very well; the model can be trained in one environment but then productionalized in completely different environment; it is not just about the code, but also about the data (features) and the model itself… At DataSentics, as a machine learning and cloud engineering studio, we see this struggle firsthand – on our internal projects and client’s projects as well.
Empowering Real Time Patient Care Through Spark StreamingDatabricks
Takeda’s Plasma Derived Therapies (PDT) business unit has recently embarked on a project to use Spark Streaming on Databricks to empower how they deliver value to their Plasma Donation centers. As patients come in and interface without clinics, we store and track all of the patient interactions in real time and deliver outputs and results based on said interactions. The current problem with our existing architecture is that it is very expensive to maintain and has an unsustainable number of failure points. Spark Streaming is essential for allowing this use case because it allows for a more robust ETL pipeline. With Spark Streaming, we are able to replace our existing ETL processes (that are based on Lamdbas, step functions, triggered jobs, etc) into a purely stream driven architecture.
Data is brought into our s3 raw layer as a large set of CSV files through AWS DMS and Informatica IICS as these services bring data from on-prem systems into our cloud layer. We have a stream currently running which takes these raw files up and merges them into Delta tables established in the bronze/stage layer. We are using AWS Glue as the metadata provider for all of these operations. From the stage layer, we have another set of streams using the stage Delta tables as their source, which transform and conduct stream to stream lookups before writing the enriched records into RDS (silver/prod layer). Once the data has been merged into RDS we have a DMS task which lifts the data back into S3 as CSV files. We have a small intermediary stream which merge these CSV files into corresponding delta tables, from which we have our gold/analytic streams. The on-prem systems are able to speak to the silver layer and allow for the near real-time latency that our patient care centers require.
This presentation describes the philosophy, the features and the future plans that we have about the Parashar21 platform of Indian Astrology
_________________________________________________________________
The new Windows Live Messenger. You don’t want to miss this.
http://www.microsoft.com/india/windows/windowslive/messenger.aspx
This document provides an overview of the Alteryx self-service data analytics platform. It describes Alteryx as a platform that combines data preparation, blending, and predictive, statistical and spatial analytics in an intuitive interface. It then discusses the different types of users of Alteryx, including data analysts, BI developers, and DBAs. Finally, it promotes trying Alteryx for free and provides a demonstration of its data preparation, blending, statistical analysis and spatial analysis capabilities using Pokémon Go datasets.
Alteryx Tutorial Step by Step Guide for BeginnersVishnuGone
Alteryx is perhaps the most well known BI stages that allows association to address business questions quickly and capably. The stage can be used as a critical construction block in an advanced change or computerization drive. Alteryx is utilized for information purifying, which has confounded characteristics between two data sources, NULL qualities, letters, or crude information and zeros in the information. Alteryx can likewise be utilized to investigate business open doors further develop independent direction. Alteryx permits us to rapidly get to, control, dissect, and yield information.
Get all about Alteryx -a data analytics automation tool.
covered in ppt-
data preparation tool
data cleansing tool
data transformation tool
in database tool
machine learning tool
AnalytiX Data Services is a data integration company founded in 2006 that provides the AnalytiX Mapping Manager solution. The Mapping Manager is a metadata and data mapping repository that automates the data mapping process and generates ETL jobs. It has over 700 customers, many of which are Fortune 1000 companies. The solution aims to accelerate project delivery by making the data mapping process faster, more manageable, and collaborative.
Data analytics is an indispensable part of modern businesses. It allows companies to make informed decisions and gain a competitive edge in their respective industries. With the proliferation of data, organizations need powerful tools to extract insights quickly and efficiently. This has led to the rise of several data analytics platforms, including Alteryx and Knime.
Smart Product Development: Scalable Solutions for Your Entire Product LifecycleAltair
Being connected to your products opens doors to recurring and value-based revenue streams. It not only solves your customer's toughest challenges; it also helps build a sustainable future for your company. Try SmartWorks IoT today, for free trial .
The document discusses Tableau and Alteryx data analytics platforms. It provides an overview of Alteryx, describing it as a self-service data analytics platform that allows users to analyze, enrich, prepare, blend, and share data using a visual workflow interface. The document also includes sections on Alteryx's market, demonstrations of its capabilities through use cases, reference customer cases, and a question and answer period.
Data flows under control tableau a& alteryx close up!Finext
The document discusses Tableau and Alteryx data analytics platforms. It provides an overview of Alteryx, describing it as a self-service data analytics platform that allows users to analyze, enrich, prepare, blend, and share data using a visual workflow interface. The document also includes sections on Alteryx's market, demonstrations of its capabilities through use cases, reference customer cases, and a question and answer period.
A dive into Microsoft Fabric/AI Solutions offering. For the event: AI, Data, and CRM: Shaping Business through Unique Experiences. By D. Koutsanastasis, Microsoft
AnalytiX DS specializes in the development of ‘agile tools’ for the data integration industry which automate manual data mapping and ETL conversion processes.
1 Introduction to Microsoft data platform analytics for releaseJen Stirrup
Part 1 of a conference workshop. This forms the morning session, which looks at moving from Business Intelligence to Analytics.
Topics Covered: Azure Data Explorer, Azure Data Factory, Azure Synapse Analytics, Event Hubs, HDInsight, Big Data
We are a IT consulting company providing services to clients across geographies in Data Engineering, AI/ML, Cloud & DevOps, Platform Engineering, and Process Hyper automation.
This document discusses data science and machine learning concepts and tools. It introduces the IBM Data Science Experience (DSX) and Watson Machine Learning (WML) products, which provide environments for data scientists and developers to build machine learning models. DSX offers notebooks, IDEs and collaboration tools, while WML focuses on visual model creation, access to algorithms, full ML workflows and APIs. It then demonstrates these products.
Qlik Sense Desktop is a free desktop analytics software that allows users to quickly create dashboards and analyses to answer business questions. It provides an associative experience to explore data through simple clicks and searches. Users can load various data sources easily using standard or custom connectors. The software features an intuitive interface for self-service data visualization and discovery. Users can create and share interactive apps with visualizations to communicate findings and collaborate.
Qlik Sense Desktop is a free desktop analytics software that allows users to quickly create dashboards and analyses to answer business questions. It provides an associative experience that allows users to explore data through simple clicks and searches. Users can load various data sources easily using standard or custom connectors. The software features an intuitive interface for creating visualizations drag and drop. It also allows sharing insights with other Qlik Sense Desktop users through storytelling capabilities.
Qlik Sense Desktop is a free desktop analytics software that allows users to quickly create dashboards and analyses to answer business questions. It provides an associative experience to explore data through simple clicks and searches. Users can load various data sources easily using standard or custom connectors. The intuitive interface allows drag-and-drop creation of visualizations that automatically update based on selections. Insights can be shared with other Qlik Sense Desktop users through storytelling features that guide others through a narrative supported by live data.
Qlik Sense Desktop is a free desktop analytics software that allows users to quickly create dashboards and analyses to answer business questions. It provides an associative experience to explore data through simple clicks and searches. Users can load various data sources easily using standard or custom connectors. The intuitive interface allows drag-and-drop creation of visualizations that automatically update based on selections. Users can share their insights through data stories and collaborate with other Qlik Sense Desktop users.
Qlik Sense Desktop is a free desktop analytics software that allows users to quickly create dashboards and analyses to answer business questions. It provides an associative experience to explore data through simple clicks and searches. Users can load various data sources easily using standard or custom connectors. The intuitive interface allows drag-and-drop creation of visualizations that automatically update based on selections. Users can share their insights through data stories and collaborate with other Qlik Sense Desktop users.
Similar to Alteryx training online for corporate (20)
IMPACT Silver is a pure silver zinc producer with over $260 million in revenue since 2008 and a large 100% owned 210km Mexico land package - 2024 catalysts includes new 14% grade zinc Plomosas mine and 20,000m of fully funded exploration drilling.
Anny Serafina Love - Letter of Recommendation by Kellen Harkins, MS.AnnySerafinaLove
This letter, written by Kellen Harkins, Course Director at Full Sail University, commends Anny Love's exemplary performance in the Video Sharing Platforms class. It highlights her dedication, willingness to challenge herself, and exceptional skills in production, editing, and marketing across various video platforms like YouTube, TikTok, and Instagram.
B2B payments are rapidly changing. Find out the 5 key questions you need to be asking yourself to be sure you are mastering B2B payments today. Learn more at www.BlueSnap.com.
Industrial Tech SW: Category Renewal and CreationChristian Dahlen
Every industrial revolution has created a new set of categories and a new set of players.
Multiple new technologies have emerged, but Samsara and C3.ai are only two companies which have gone public so far.
Manufacturing startups constitute the largest pipeline share of unicorns and IPO candidates in the SF Bay Area, and software startups dominate in Germany.
The Evolution and Impact of OTT Platforms: A Deep Dive into the Future of Ent...ABHILASH DUTTA
This presentation provides a thorough examination of Over-the-Top (OTT) platforms, focusing on their development and substantial influence on the entertainment industry, with a particular emphasis on the Indian market.We begin with an introduction to OTT platforms, defining them as streaming services that deliver content directly over the internet, bypassing traditional broadcast channels. These platforms offer a variety of content, including movies, TV shows, and original productions, allowing users to access content on-demand across multiple devices.The historical context covers the early days of streaming, starting with Netflix's inception in 1997 as a DVD rental service and its transition to streaming in 2007. The presentation also highlights India's television journey, from the launch of Doordarshan in 1959 to the introduction of Direct-to-Home (DTH) satellite television in 2000, which expanded viewing choices and set the stage for the rise of OTT platforms like Big Flix, Ditto TV, Sony LIV, Hotstar, and Netflix. The business models of OTT platforms are explored in detail. Subscription Video on Demand (SVOD) models, exemplified by Netflix and Amazon Prime Video, offer unlimited content access for a monthly fee. Transactional Video on Demand (TVOD) models, like iTunes and Sky Box Office, allow users to pay for individual pieces of content. Advertising-Based Video on Demand (AVOD) models, such as YouTube and Facebook Watch, provide free content supported by advertisements. Hybrid models combine elements of SVOD and AVOD, offering flexibility to cater to diverse audience preferences.
Content acquisition strategies are also discussed, highlighting the dual approach of purchasing broadcasting rights for existing films and TV shows and investing in original content production. This section underscores the importance of a robust content library in attracting and retaining subscribers.The presentation addresses the challenges faced by OTT platforms, including the unpredictability of content acquisition and audience preferences. It emphasizes the difficulty of balancing content investment with returns in a competitive market, the high costs associated with marketing, and the need for continuous innovation and adaptation to stay relevant.
The impact of OTT platforms on the Bollywood film industry is significant. The competition for viewers has led to a decrease in cinema ticket sales, affecting the revenue of Bollywood films that traditionally rely on theatrical releases. Additionally, OTT platforms now pay less for film rights due to the uncertain success of films in cinemas.
Looking ahead, the future of OTT in India appears promising. The market is expected to grow by 20% annually, reaching a value of ₹1200 billion by the end of the decade. The increasing availability of affordable smartphones and internet access will drive this growth, making OTT platforms a primary source of entertainment for many viewers.
Understanding User Needs and Satisfying ThemAggregage
https://www.productmanagementtoday.com/frs/26903918/understanding-user-needs-and-satisfying-them
We know we want to create products which our customers find to be valuable. Whether we label it as customer-centric or product-led depends on how long we've been doing product management. There are three challenges we face when doing this. The obvious challenge is figuring out what our users need; the non-obvious challenges are in creating a shared understanding of those needs and in sensing if what we're doing is meeting those needs.
In this webinar, we won't focus on the research methods for discovering user-needs. We will focus on synthesis of the needs we discover, communication and alignment tools, and how we operationalize addressing those needs.
Industry expert Scott Sehlhorst will:
• Introduce a taxonomy for user goals with real world examples
• Present the Onion Diagram, a tool for contextualizing task-level goals
• Illustrate how customer journey maps capture activity-level and task-level goals
• Demonstrate the best approach to selection and prioritization of user-goals to address
• Highlight the crucial benchmarks, observable changes, in ensuring fulfillment of customer needs
Storytelling is an incredibly valuable tool to share data and information. To get the most impact from stories there are a number of key ingredients. These are based on science and human nature. Using these elements in a story you can deliver information impactfully, ensure action and drive change.
Taurus Zodiac Sign: Unveiling the Traits, Dates, and Horoscope Insights of th...my Pandit
Dive into the steadfast world of the Taurus Zodiac Sign. Discover the grounded, stable, and logical nature of Taurus individuals, and explore their key personality traits, important dates, and horoscope insights. Learn how the determination and patience of the Taurus sign make them the rock-steady achievers and anchors of the zodiac.
Zodiac Signs and Food Preferences_ What Your Sign Says About Your Tastemy Pandit
Know what your zodiac sign says about your taste in food! Explore how the 12 zodiac signs influence your culinary preferences with insights from MyPandit. Dive into astrology and flavors!
Structural Design Process: Step-by-Step Guide for BuildingsChandresh Chudasama
The structural design process is explained: Follow our step-by-step guide to understand building design intricacies and ensure structural integrity. Learn how to build wonderful buildings with the help of our detailed information. Learn how to create structures with durability and reliability and also gain insights on ways of managing structures.
At Techbox Square, in Singapore, we're not just creative web designers and developers, we're the driving force behind your brand identity. Contact us today.
How MJ Global Leads the Packaging Industry.pdfMJ Global
MJ Global's success in staying ahead of the curve in the packaging industry is a testament to its dedication to innovation, sustainability, and customer-centricity. By embracing technological advancements, leading in eco-friendly solutions, collaborating with industry leaders, and adapting to evolving consumer preferences, MJ Global continues to set new standards in the packaging sector.
Event Report - SAP Sapphire 2024 Orlando - lots of innovation and old challengesHolger Mueller
Holger Mueller of Constellation Research shares his key takeaways from SAP's Sapphire confernece, held in Orlando, June 3rd till 5th 2024, in the Orange Convention Center.
Event Report - SAP Sapphire 2024 Orlando - lots of innovation and old challenges
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