Get all about Alteryx -a data analytics automation tool.
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data preparation tool
data cleansing tool
data transformation tool
in database tool
machine learning tool
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.
Agile Testing Days 2017 Intoducing AgileBI Sustainably - ExcercisesRaphael Branger
"We now do Agile BI too” is often heard in todays BI community. But can you really "create" agile in Business Intelligence projects? This presentation shows that Agile BI doesn't necessarily start with the introduction of an iterative project approach. An organisation is well advised to establish first the necessary foundations in regards to organisation, business and technology in order to become capable of an iterative, incremental project approach in the BI domain.
In this session you learn which building blocks you need to consider. In addition you will see what a meaningful sequence to these building blocks is. Selected aspects like test automation, BI specific design patterns as well as the Disciplined Agile Framework will be explained in more and practical details.
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.
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/
Intro of Key Features of SoftCAAT BI Softwarerafeq
This presentation provides a brief overview of SoftCAAT BI with use cases. SoftCAAT BI is a Data Analytics/BI/MIS software specially designed for performing analytics in the assignments of Assurance, Compliance, Consulting and Fraud Investigations.
12 Pro Predictive Analysis Tools to Look Out for in 2024.pdfCIOWomenMagazine
Here are some predictive analysis tools: 1. Tableau Predictive Analytics, 2. IBM Watson Studio, 3. Alteryx Predictive Analytics, 4. RapidMiner, 5. SAS Predictive Analytics, etc.
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.
Agile Testing Days 2017 Intoducing AgileBI Sustainably - ExcercisesRaphael Branger
"We now do Agile BI too” is often heard in todays BI community. But can you really "create" agile in Business Intelligence projects? This presentation shows that Agile BI doesn't necessarily start with the introduction of an iterative project approach. An organisation is well advised to establish first the necessary foundations in regards to organisation, business and technology in order to become capable of an iterative, incremental project approach in the BI domain.
In this session you learn which building blocks you need to consider. In addition you will see what a meaningful sequence to these building blocks is. Selected aspects like test automation, BI specific design patterns as well as the Disciplined Agile Framework will be explained in more and practical details.
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.
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/
Intro of Key Features of SoftCAAT BI Softwarerafeq
This presentation provides a brief overview of SoftCAAT BI with use cases. SoftCAAT BI is a Data Analytics/BI/MIS software specially designed for performing analytics in the assignments of Assurance, Compliance, Consulting and Fraud Investigations.
12 Pro Predictive Analysis Tools to Look Out for in 2024.pdfCIOWomenMagazine
Here are some predictive analysis tools: 1. Tableau Predictive Analytics, 2. IBM Watson Studio, 3. Alteryx Predictive Analytics, 4. RapidMiner, 5. SAS Predictive Analytics, etc.
Knowledge Studio text analytics add-on is an industry-first application that combines visual text discovery and sentiment analysis with the power of predictive analytics. It delivers unparalleled voice of the customer insights to support customer experience management.
Accenture migrated its analytics platform from an on-premise system to Google Cloud's Platform-as-a-Service model to address challenges around scalability, costs, and maintenance. This involved modernizing Accenture's data architecture and migrating over 400 terabytes of data and 50+ applications. The transition unlocked new analytics capabilities, increased cost savings through Google Cloud's pay-as-you-go model, and improved performance. Accenture also focused on developing its employees' cloud skills to support the new platform and drive business value from data insights.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricCambridge Semantics
Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
How to Identify, Train or Become a Data ScientistInside Analysis
The Briefing Room with Neil Raden and Actian
Live Webcast Sept. 3, 2013
Visit: www.insideanalysis.com
Respected research institutes keep saying we have a shortage of data scientists, which makes sense because the title is so new. But most business analysts and serious data managers have at least some of the necessary training to fill this new role. And any number of curious, diligent professionals can learn how to be a data scientist, if they can get access to the right tools and education.
Register for this episode of The Briefing Room to hear veteran Analyst Neil Raden of Hired Brains offer insights about how to identify the key characteristics of a data scientist role. He'll then explain how professionals can incrementally improve their data science skills. He'll be briefed by John Santaferraro of Actian, who will showcase his company's Data Flow Engine, which provides unprecedented visual access to highly complex data flows. This, coupled with Actian's multiple analytics database technologies, opens the door to whole new avenues of possible insights.
Rajesh Manjunath has over 19 years of experience in data analytics and business intelligence. He has extensive experience in data strategy, data warehousing, big data solutions, and data science. Currently he works as a Data Science Associate at Cisco Systems, where he focuses on areas like data science workbench, data visualization, predictive modeling, and machine learning. He has successfully delivered many analytics projects and initiatives over his career to help organizations drive business outcomes through data-driven insights.
Intro of Key Features of SoftCAAT Ent SQL Softwarerafeq
This presentation provides a brief overview of SoftCAAT Ent SQL Version software with use cases. SoftCAAT is a Data analytics/BI software which can used for performing complex analytics on large voluem of data in SQL. SoftCAAT is primarily used by CAs and CXOs for Assurance/BI/MIS, Compliance and Fraud Investigations.
Data science Nagarajan and madhav.pptxNagarajanG35
This document summarizes a presentation on data science. It includes details about the presenters, date, time and login details for a seminar on data science. It then provides definitions and explanations of key concepts in data science including machine learning, deep learning, statistics and visualization. It describes common data science jobs and roles and lists popular tools used in data science. Finally, it discusses applications of data science and some challenges in the field.
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.
Cloud analytics is a service model where elements of the data analytics process are provided through public or private clouds. These services are typically offered on a subscription or pay-per-use basis. Examples include hosted data warehouses, SaaS BI, and social media analytics. Cloud analytics competencies that support clients include analytics strategy, business intelligence, analytics and optimization, and content management. Cloud analytics works by combining hardware, middleware, and platforms that provide data reporting, analytics techniques, storage optimization, and data warehouse management. Benefits include getting the right information when needed, identifying information sources, and designing policies faster to increase profits, reduce cycle times, and reduce defects.
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.
Data Science Salon: Applying Machine Learning to Modernize Business ProcessesFormulatedby
Next DSS MIA Event - https://datascience.salon/miami/
For most data scientist building models is hard work, but deploying them into production and impacting business processes can be even harder. In fact, research shows that only about 10% of data science models get deployed into production, and those that do can take between 6 to 9 months to be deployed. This session will highlight the challenges that data scientist and organizations alike face when trying to deploy machine learning models and how to overcome these challenges. It will examine several use cases where models built in R and Python have been able to deliver impactful results across several industries.
Dibyajyoti Bose is a senior data scientist with over 10 years of experience in data analytics and business intelligence. He has extensive experience managing analytics projects, developing predictive models using machine learning techniques, and creating visualizations and reports. His skills include R, SAS, Tableau, Hadoop, and machine learning algorithms. He has worked on projects in various domains for clients in the US, UK, and India.
The document provides an executive summary and details for Abhishek Jaiswal, including his contact information, over 8 years of experience in business intelligence, data warehousing, and data integration. It lists his technical skills and tools used, as well as details of various projects he has worked on in roles such as technical lead and senior software engineer. Projects include building master customer databases, data migration, and dashboard and reporting solutions.
AI Project Management and Workflow Automation.pdfTopLinkSeo
The document discusses how AI is revolutionizing project management, workflow automation, and team collaboration. It describes how AI enhances efficiency, data-driven decision making, and predictive analytics in project management. AI powers automated project planning, real-time monitoring, and intelligent resource allocation. For workflow automation, AI handles repetitive tasks to reduce errors and adapt to changes. When combined with AI project management, workflow automation streamlines documentation and collaboration. The document also explains how AI improves communication, task coordination, and idea generation to enhance team performance. Real-world examples demonstrate benefits like reduced timelines and increased productivity and innovation.
Big data journey to the cloud maz chaudhri 5.30.18Cloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
Data Analytics & Engineering Staffing Solutions | NLB ServicesNLB Services
We provide top-notch digital solutions with data analytics & data engineering staffing services. We help firms unlock growth prospects. Know more us at https://nlbservices.com/data-analytics-and-engineering/
This document provides summaries of trends in IT, including cloud computing, business analytics, artificial intelligence and machine learning, and database management systems. It discusses how cloud computing allows users to access computing resources over the internet rather than owning hardware. It also explains how business analytics uses data and modeling to help businesses make decisions, and how artificial intelligence and machine learning use algorithms to enable machines to learn from data and mimic human behavior. Finally, it defines a database management system as software that interfaces with databases and allows users to organize, access, and manage data.
AnalytiX DS specializes in the development of ‘agile tools’ for the data integration industry which automate manual data mapping and ETL conversion processes.
At iStream, our vision is to empower businesses and organizations by harnessing the intelligence of data analytics using open source technologies and platforms.
Our i360 intelligence suite will enable businesses to enhance their organization’s strategies based on data-driven deployments, effectively turning data into business decisions and smarter strategies.
Dedicated to our client’s success, we are driven by innovation that matters and our solutions are developed to enable organisations to focus their efforts on more pertinent issues, to gain a sustainable edge in driving business and organisational innovations.
i360 @ Kuala Lumpur, Malaysia
Knowledge Studio text analytics add-on is an industry-first application that combines visual text discovery and sentiment analysis with the power of predictive analytics. It delivers unparalleled voice of the customer insights to support customer experience management.
Accenture migrated its analytics platform from an on-premise system to Google Cloud's Platform-as-a-Service model to address challenges around scalability, costs, and maintenance. This involved modernizing Accenture's data architecture and migrating over 400 terabytes of data and 50+ applications. The transition unlocked new analytics capabilities, increased cost savings through Google Cloud's pay-as-you-go model, and improved performance. Accenture also focused on developing its employees' cloud skills to support the new platform and drive business value from data insights.
How a Semantic Layer Makes Data Mesh Work at ScaleDATAVERSITY
Data Mesh is a trending approach to building a decentralized data architecture by leveraging a domain-oriented, self-service design. However, the pure definition of Data Mesh lacks a center of excellence or central data team and doesn’t address the need for a common approach for sharing data products across teams. The semantic layer is emerging as a key component to supporting a Hub and Spoke style of organizing data teams by introducing data model sharing, collaboration, and distributed ownership controls.
This session will explain how data teams can define common models and definitions with a semantic layer to decentralize analytics product creation using a Hub and Spoke architecture.
Attend this session to learn about:
- The role of a Data Mesh in the modern cloud architecture.
- How a semantic layer can serve as the binding agent to support decentralization.
- How to drive self service with consistency and control.
Using a Semantic and Graph-based Data Catalog in a Modern Data FabricCambridge Semantics
Watch this webinar to learn about the benefits of using semantic and graph database technology to create a Data Catalog of all of an enterprise's data, regardless of source or format, as part of a modern IT or data management stack and an important step toward building an Enterprise Data Fabric.
How to Identify, Train or Become a Data ScientistInside Analysis
The Briefing Room with Neil Raden and Actian
Live Webcast Sept. 3, 2013
Visit: www.insideanalysis.com
Respected research institutes keep saying we have a shortage of data scientists, which makes sense because the title is so new. But most business analysts and serious data managers have at least some of the necessary training to fill this new role. And any number of curious, diligent professionals can learn how to be a data scientist, if they can get access to the right tools and education.
Register for this episode of The Briefing Room to hear veteran Analyst Neil Raden of Hired Brains offer insights about how to identify the key characteristics of a data scientist role. He'll then explain how professionals can incrementally improve their data science skills. He'll be briefed by John Santaferraro of Actian, who will showcase his company's Data Flow Engine, which provides unprecedented visual access to highly complex data flows. This, coupled with Actian's multiple analytics database technologies, opens the door to whole new avenues of possible insights.
Rajesh Manjunath has over 19 years of experience in data analytics and business intelligence. He has extensive experience in data strategy, data warehousing, big data solutions, and data science. Currently he works as a Data Science Associate at Cisco Systems, where he focuses on areas like data science workbench, data visualization, predictive modeling, and machine learning. He has successfully delivered many analytics projects and initiatives over his career to help organizations drive business outcomes through data-driven insights.
Intro of Key Features of SoftCAAT Ent SQL Softwarerafeq
This presentation provides a brief overview of SoftCAAT Ent SQL Version software with use cases. SoftCAAT is a Data analytics/BI software which can used for performing complex analytics on large voluem of data in SQL. SoftCAAT is primarily used by CAs and CXOs for Assurance/BI/MIS, Compliance and Fraud Investigations.
Data science Nagarajan and madhav.pptxNagarajanG35
This document summarizes a presentation on data science. It includes details about the presenters, date, time and login details for a seminar on data science. It then provides definitions and explanations of key concepts in data science including machine learning, deep learning, statistics and visualization. It describes common data science jobs and roles and lists popular tools used in data science. Finally, it discusses applications of data science and some challenges in the field.
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.
Cloud analytics is a service model where elements of the data analytics process are provided through public or private clouds. These services are typically offered on a subscription or pay-per-use basis. Examples include hosted data warehouses, SaaS BI, and social media analytics. Cloud analytics competencies that support clients include analytics strategy, business intelligence, analytics and optimization, and content management. Cloud analytics works by combining hardware, middleware, and platforms that provide data reporting, analytics techniques, storage optimization, and data warehouse management. Benefits include getting the right information when needed, identifying information sources, and designing policies faster to increase profits, reduce cycle times, and reduce defects.
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.
Data Science Salon: Applying Machine Learning to Modernize Business ProcessesFormulatedby
Next DSS MIA Event - https://datascience.salon/miami/
For most data scientist building models is hard work, but deploying them into production and impacting business processes can be even harder. In fact, research shows that only about 10% of data science models get deployed into production, and those that do can take between 6 to 9 months to be deployed. This session will highlight the challenges that data scientist and organizations alike face when trying to deploy machine learning models and how to overcome these challenges. It will examine several use cases where models built in R and Python have been able to deliver impactful results across several industries.
Dibyajyoti Bose is a senior data scientist with over 10 years of experience in data analytics and business intelligence. He has extensive experience managing analytics projects, developing predictive models using machine learning techniques, and creating visualizations and reports. His skills include R, SAS, Tableau, Hadoop, and machine learning algorithms. He has worked on projects in various domains for clients in the US, UK, and India.
The document provides an executive summary and details for Abhishek Jaiswal, including his contact information, over 8 years of experience in business intelligence, data warehousing, and data integration. It lists his technical skills and tools used, as well as details of various projects he has worked on in roles such as technical lead and senior software engineer. Projects include building master customer databases, data migration, and dashboard and reporting solutions.
AI Project Management and Workflow Automation.pdfTopLinkSeo
The document discusses how AI is revolutionizing project management, workflow automation, and team collaboration. It describes how AI enhances efficiency, data-driven decision making, and predictive analytics in project management. AI powers automated project planning, real-time monitoring, and intelligent resource allocation. For workflow automation, AI handles repetitive tasks to reduce errors and adapt to changes. When combined with AI project management, workflow automation streamlines documentation and collaboration. The document also explains how AI improves communication, task coordination, and idea generation to enhance team performance. Real-world examples demonstrate benefits like reduced timelines and increased productivity and innovation.
Big data journey to the cloud maz chaudhri 5.30.18Cloudera, Inc.
We hope this session was valuable in teaching you more about Cloudera Enterprise on AWS, and how fast and easy it is to deploy a modern data management platform—in your cloud and on your terms.
Data Analytics & Engineering Staffing Solutions | NLB ServicesNLB Services
We provide top-notch digital solutions with data analytics & data engineering staffing services. We help firms unlock growth prospects. Know more us at https://nlbservices.com/data-analytics-and-engineering/
This document provides summaries of trends in IT, including cloud computing, business analytics, artificial intelligence and machine learning, and database management systems. It discusses how cloud computing allows users to access computing resources over the internet rather than owning hardware. It also explains how business analytics uses data and modeling to help businesses make decisions, and how artificial intelligence and machine learning use algorithms to enable machines to learn from data and mimic human behavior. Finally, it defines a database management system as software that interfaces with databases and allows users to organize, access, and manage data.
AnalytiX DS specializes in the development of ‘agile tools’ for the data integration industry which automate manual data mapping and ETL conversion processes.
At iStream, our vision is to empower businesses and organizations by harnessing the intelligence of data analytics using open source technologies and platforms.
Our i360 intelligence suite will enable businesses to enhance their organization’s strategies based on data-driven deployments, effectively turning data into business decisions and smarter strategies.
Dedicated to our client’s success, we are driven by innovation that matters and our solutions are developed to enable organisations to focus their efforts on more pertinent issues, to gain a sustainable edge in driving business and organisational innovations.
i360 @ Kuala Lumpur, Malaysia
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2. Program Name:B.Tech
Introduction to Alteryx
Alteryx stands at the forefront, offering a comprehensive platform that
empowers data professionals to seamlessly blend, analyze, and automate
data workflows. With its user-friendly interface and robust toolkit.
Alteryx is redefining the way businesses harness the potential of their data.
7. Program Name:B.Tech
Transforming Data into Actionable
Insights
Data Blending: Alteryx seamlessly integrates and analyzes data from multiple sources,
providing a holistic view that leads to more informed decision-making.
Workflow Automation: Say goodbye to manual, repetitive tasks. Alteryx enables the automation
of workflows, saving time and allowing teams to focus on strategic initiatives.
Predictive Analytics: With Alteryx, organizations can harness the power of predictive modeling
to anticipate trends, identify patterns, and make proactive decisions.
Scalability: Alteryx is designed to handle large datasets efficiently, ensuring that data
professionals can scale their analytics efforts as the business grows.
User-Friendly Interface: The intuitive design of Alteryx's interface empowers both analysts and
data scientists to navigate complex data processes with ease, fostering collaboration and
efficiency.
8. Program Name:B.Tech
Alteryx Use Cases
Solving Real-World Challenges
.
Financial Analysis:
Risk assessment and fraud detection.
Marketing Optimization: Targeted campaigns and
customer segmentation.
Human Resources: Employee
performance analysis and workforce
planning
Supply Chain Management:
Forecasting and optimization.
Healthcare Analytics: Patient outcomes and resource allocation.