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
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/
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.
Business Intelligence Barista: What DataViz Tool to Use, and When?Jen Stirrup
Choosing a data visualization tool is like being a barista serving coffee: everyone wants their data, their way, personalized, fast, and perfect. Many organizations have a cottage industry of data visualization tools, and it's difficult to know what tool to use, and when. Different tools exist in different departments, and if it doesn't meet the user requirements, the default position is to go back to Excel and move the data around there.
This session will examine data visualization tools such as SSRS Excel, Tableau, QlikView, Datazen, Kibana and PowerBI, in order to craft and blend your data visualization tools to serve your data customers better.
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/
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.
Business Intelligence Barista: What DataViz Tool to Use, and When?Jen Stirrup
Choosing a data visualization tool is like being a barista serving coffee: everyone wants their data, their way, personalized, fast, and perfect. Many organizations have a cottage industry of data visualization tools, and it's difficult to know what tool to use, and when. Different tools exist in different departments, and if it doesn't meet the user requirements, the default position is to go back to Excel and move the data around there.
This session will examine data visualization tools such as SSRS Excel, Tableau, QlikView, Datazen, Kibana and PowerBI, in order to craft and blend your data visualization tools to serve your data customers better.
Splunk Announces Beta Version of Hunk: Splunk Analytics for Hadoop
New Software Product to Explore, Analyze and Visualize Data in Hadoop
HADOOP SUMMIT NORTH AMERICA 2013, SAN JOSE – June 26, 2013 - Splunk Inc. (NASDAQ: SPLK), the leading software platform for real-time operational intelligence, today announced the beta version of Hunk: Splunk® Analytics for Hadoop. Hunk (beta) is a new software product from Splunk that integrates exploration, analysis and visualization of data in Hadoop. Building upon Splunk’s years of experience with big data analytics technology deployed at thousands of customers, Hunk drives dramatic improvements in the speed and simplicity of interacting with and analyzing data in Hadoop without programming, costly integrations or forced data migrations. Watch the Hunk video to learn more.
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/
Data Lakes on Public Cloud: Breaking Data Management MonolithsItai Yaffe
Sharon Dashet (Sr. Data Analytics Solution Lead) @ Google Cloud:
The worlds of traditional RDBMS and Data Lake Hadoop systems are converging and moving to public cloud and SaaS offerings.
In this session, Sharon will share her personal journey as a data professional since the 90s weaved into the history of data management systems.
The session will also cover the differences between on-premise and cloud Data Lakes.
f you have any further questions, please don't hesitate to contact me. Please feel free to call me on (telephone) or contact by (email), if you require any further information.
DataLakes kan skalere i takt med skyen, nedbryde integrationsbarrierer og data gemt i siloer og bane vejen for nye forretningsmuligheder. Det er alt sammen med til at give et bedre beslutningsgrundlag for ledelse og medarbejdere. Kom og hør hvordan.
David Bojsen, Arkitekt, Microsoft
Turn Data Into Actionable Insights - StampedeCon 2016StampedeCon
At Monsanto, emerging technologies such as IoT, advanced imaging and geo-spatial platforms; molecular breeding, ancestry and genomics data sets have made us rethink how we approach developing, deploying, scaling and distributing our software to accelerate predictive and prescriptive decisions. We created a Cloud based Data Science platform for the enterprise to address this need. Our primary goals were to perform analytics@scale and integrate analytics with our core product platforms.
As part of this talk, we will be sharing our journey of transformation showing how we enabled: a collaborative discovery analytics environment for data science teams to perform model development, provisioning data through APIs, streams and deploying models to production through our auto-scaling big-data compute in the cloud to perform streaming, cognitive, predictive, prescriptive, historical and batch analytics@scale, integrating analytics with our core product platforms to turn data into actionable insights.
ADV Slides: What the Aspiring or New Data Scientist Needs to Know About the E...DATAVERSITY
Many data scientists are well grounded in creating accomplishment in the enterprise, but many come from outside – from academia, from PhD programs and research. They have the necessary technical skills, but it doesn’t count until their product gets to production and in use. The speaker recently helped a struggling data scientist understand his organization and how to create success in it. That turned into this presentation, because many new data scientists struggle with the complexities of an enterprise.
Splunk Announces Beta Version of Hunk: Splunk Analytics for Hadoop
New Software Product to Explore, Analyze and Visualize Data in Hadoop
HADOOP SUMMIT NORTH AMERICA 2013, SAN JOSE – June 26, 2013 - Splunk Inc. (NASDAQ: SPLK), the leading software platform for real-time operational intelligence, today announced the beta version of Hunk: Splunk® Analytics for Hadoop. Hunk (beta) is a new software product from Splunk that integrates exploration, analysis and visualization of data in Hadoop. Building upon Splunk’s years of experience with big data analytics technology deployed at thousands of customers, Hunk drives dramatic improvements in the speed and simplicity of interacting with and analyzing data in Hadoop without programming, costly integrations or forced data migrations. Watch the Hunk video to learn more.
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/
Data Lakes on Public Cloud: Breaking Data Management MonolithsItai Yaffe
Sharon Dashet (Sr. Data Analytics Solution Lead) @ Google Cloud:
The worlds of traditional RDBMS and Data Lake Hadoop systems are converging and moving to public cloud and SaaS offerings.
In this session, Sharon will share her personal journey as a data professional since the 90s weaved into the history of data management systems.
The session will also cover the differences between on-premise and cloud Data Lakes.
f you have any further questions, please don't hesitate to contact me. Please feel free to call me on (telephone) or contact by (email), if you require any further information.
DataLakes kan skalere i takt med skyen, nedbryde integrationsbarrierer og data gemt i siloer og bane vejen for nye forretningsmuligheder. Det er alt sammen med til at give et bedre beslutningsgrundlag for ledelse og medarbejdere. Kom og hør hvordan.
David Bojsen, Arkitekt, Microsoft
Turn Data Into Actionable Insights - StampedeCon 2016StampedeCon
At Monsanto, emerging technologies such as IoT, advanced imaging and geo-spatial platforms; molecular breeding, ancestry and genomics data sets have made us rethink how we approach developing, deploying, scaling and distributing our software to accelerate predictive and prescriptive decisions. We created a Cloud based Data Science platform for the enterprise to address this need. Our primary goals were to perform analytics@scale and integrate analytics with our core product platforms.
As part of this talk, we will be sharing our journey of transformation showing how we enabled: a collaborative discovery analytics environment for data science teams to perform model development, provisioning data through APIs, streams and deploying models to production through our auto-scaling big-data compute in the cloud to perform streaming, cognitive, predictive, prescriptive, historical and batch analytics@scale, integrating analytics with our core product platforms to turn data into actionable insights.
ADV Slides: What the Aspiring or New Data Scientist Needs to Know About the E...DATAVERSITY
Many data scientists are well grounded in creating accomplishment in the enterprise, but many come from outside – from academia, from PhD programs and research. They have the necessary technical skills, but it doesn’t count until their product gets to production and in use. The speaker recently helped a struggling data scientist understand his organization and how to create success in it. That turned into this presentation, because many new data scientists struggle with the complexities of an enterprise.
Advanced Analytics and Machine Learning with Data Virtualization (India)Denodo
Watch full webinar here: https://bit.ly/3dMN503
Advanced data science techniques, like machine learning, have proven an extremely useful tool to derive valuable insights from existing data. Platforms like Spark, and complex libraries for R, Python, and Scala put advanced techniques at the fingertips of the data scientists. However, these data scientists spend most of their time looking for the right data and massaging it into a usable format. Data virtualization offers a new alternative to address these issues in a more efficient and agile way.
Watch this session to learn how companies can use data virtualization to:
- Create a logical architecture to make all enterprise data available for advanced analytics exercise
- Accelerate data acquisition and massaging, providing the data scientist with a powerful tool to complement their practice
- Integrate popular tools from the data science ecosystem: Spark, Python, Zeppelin, Jupyter, etc
It is a fascinating, explosive time for enterprise analytics.
It is from the position of analytics leadership that the mission will be executed and company leadership will emerge. The data professional is absolutely sitting on the performance of the company in this information economy and has an obligation to demonstrate the possibilities and originate the architecture, data, and projects that will deliver analytics. After all, no matter what business you’re in, you’re in the business of analytics.
The coming years will be full of big changes in enterprise analytics and Data Architecture. William will kick off the fourth year of the Advanced Analytics series with a discussion of the trends winning organizations should build into their plans, expectations, vision, and awareness now.
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.
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.
Oracle Analytics Cloud (OAC), its features & products by Tangenz Corporation.
Discover the capabilities your organization can achieve by OAC Implementation.
Learn more: https://tangenz.com/data-actions-in-oracle-analytics-cloud-oac/
IoT - Retour d'expérience de projets clients dans le domaine IoT. Michael Epprecht, Technical Specialist in the Global Black Belt IoT Team at Microsoft. Conférence donnée dans le cadre du Swiss Data Forum, du 24 novembre 2015 à Lausanne
QuerySurge Slide Deck for Big Data Testing WebinarRTTS
This is a slide deck from QuerySurge's Big Data Testing webinar.
Learn why Testing is pivotal to the success of your Big Data Strategy .
Learn more at www.querysurge.com
The growing variety of new data sources is pushing organizations to look for streamlined ways to manage complexities and get the most out of their data-related investments. The companies that do this correctly are realizing the power of big data for business expansion and growth.
Learn why testing your enterprise's data is pivotal for success with big data, Hadoop and NoSQL. Learn how to increase your testing speed, boost your testing coverage (up to 100%), and improve the level of quality within your data warehouse - all with one ETL testing tool.
This information is geared towards:
- Big Data & Data Warehouse Architects,
- ETL Developers
- ETL Testers, Big Data Testers
- Data Analysts
- Operations teams
- Business Intelligence (BI) Architects
- Data Management Officers & Directors
You will learn how to:
- Improve your Data Quality
- Accelerate your data testing cycles
- Reduce your costs & risks
- Provide a huge ROI (as high as 1,300%)
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
Denodo DataFest 2016: Big Data Virtualization in the CloudDenodo
Watch the full session: Denodo DataFest 2016 sessions: https://goo.gl/kahTgf
Many firms are adopting “cloud first” strategy and are migrating their on-premises technologies to the cloud. Logitech is one of them. They have adopted the AWS platform and big data on the cloud for all of their analytical needs, including Amazon Redshift and S3.
In this presentation, the Principal of Big Data and Analytics team at Logitech, Avinash Deshpande will present:
• The business rationale for migrating to the cloud
• How data virtualization enables the migration
• Running data virtualization itself in the cloud
This session also includes a panel discussion with:
• Avinash Deshpande, Principal – Big Data and Analytics at Logitech
• Kurt Jackson, Platform Lead at Autodesk
• Dan Young, Chief Data Architect at Indiana University
• Paul Moxon, Head of Product Management at Denodo (as moderator)
This session is part of the Denodo DataFest 2016 event. You can also watch more Denodo DataFest sessions on demand here: https://goo.gl/VXb6M6
Nov 2014 talk to SW Data Meetup by Mike Olson, co-founder and chairman of Cloudera.
In business, we often deal with hype around trends in society, politics, economy and technology. We know we need to take claims of the next big thing with a grain of salt and that we should be careful not to set expectations too high. However, with Big Data analytics, the opposite is true. The hype that accompanies it actually conceals the enormity of its impact on the way we do business. In this talk I’ll discuss how new 'Data Driven' economies are emerging through relentless innovation across the public and private sectors.
Mike (co-founded Cloudera in 2008 and served as its CEO until 2013 when he took on his current role of chief strategy officer (CSO.) As CSO, Mike is responsible for Cloudera’s product strategy, open source leadership, engineering alignment and direct engagement with customers. Prior to Cloudera Mike was CEO of Sleepycat Software, makers of Berkeley DB, the open source embedded database engine. Mike spent two years at Oracle Corporation as vice president for Embedded Technologies after Oracle’s acquisition of Sleepycat in 2006. Prior to joining Sleepycat, Mike held technical and business positions at database vendors Britton Lee, Illustra Information Technologies and Informix Software. Mike has a Bachelor’s and a Master’s Degree in Computer Science from the University of California, Berkeley.
Similar to Here are some of the things our Data Analytics team can do (20)
In many countries, motorcycles are primarily used for recreation. However, in Colombia they also serve as basic transportation for millions. Steep hills and mountains, rainy weather, and sometimes, unpaved roads create challenges for motorcyclists. With this in mind, the Minister of Transportation, Guillermo Francisco Reyes Gonzalez signed into law resolution 20223040062115 dated October 13, 2022 mandating new safety standards for motorcycles sold in the Andean nation.
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JOHN CAM ILO A GUILAR JARM ILLO,
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Trinidad & Tobago Breaks Through Into Top Tier of Global Services DestinationsLoren Moss
The global landscape for service delivery, whether Business Process Outsourcing (BPO) or in-house shared services is never static. Global executives in the process of shortlisting locations are unwise to simply return to the default choices of a decade ago. Things change. There is no better proof of this than the twin-island nation of Trinidad & Tobago making a striking first appearance on A.T. Kearney’s recent ranking of the world’s most desirable global service delivery locations in their 2016 A.T. Kearney Global Services Location Index.
Latin America's Role in driving "Americas-Centric" Outsourcing & U.S. Competi...Loren Moss
U.S. businesses want to improve efficiencies, accelerate technical innovation and gear their businesses to be globally ready – and the Latin America IT/ BPO marketplace is starting to recognize these requirements, creating an ideal environment for ‘Americas-centric’ outsourcing.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Adjusting primitives for graph : SHORT REPORT / NOTESSubhajit Sahu
Graph algorithms, like PageRank Compressed Sparse Row (CSR) is an adjacency-list based graph representation that is
Multiply with different modes (map)
1. Performance of sequential execution based vs OpenMP based vector multiply.
2. Comparing various launch configs for CUDA based vector multiply.
Sum with different storage types (reduce)
1. Performance of vector element sum using float vs bfloat16 as the storage type.
Sum with different modes (reduce)
1. Performance of sequential execution based vs OpenMP based vector element sum.
2. Performance of memcpy vs in-place based CUDA based vector element sum.
3. Comparing various launch configs for CUDA based vector element sum (memcpy).
4. Comparing various launch configs for CUDA based vector element sum (in-place).
Sum with in-place strategies of CUDA mode (reduce)
1. Comparing various launch configs for CUDA based vector element sum (in-place).
Here are some of the things our Data Analytics team can do
1. What we can do as
data analysts
By: Estefania, Pablo andVictor
2. What is Alteryx?
Alteryx is a software capable
of data blending and
advanced data analytics. It
has a stated goal of enabling
advanced analytics to be
performed by non-
specialists.
3.
4. Strengths and Capabilities
• Data cleansing
• Data parsing (with RegEx) for
example
• Join many datasets
• Statistical, financial, spatial
and demographic analysis
• Prep and blend data
• Create reports
• JSON Parsing
• API calls
• Create batch macros for multiple
uses
• Fuzzy matching for data
segmentation
• SQL
5. Advantages
• Makes your data more searchable and trackable
• Unlock all your datasets - big or small, clean or dirty. No waiting. No coding
• Connect, profile, prep, and blend all your data, wherever it's stored - on your desktop, in the cloud, hidden
in legacy systems - just disparate data all flowing together, making sense, and sustaining more answers
• Thanks to the visual repeatable workflows, no more wasting time doing the same data prep over and over
again
• Create powerful statistical, demographic and spatial models using repeatable workflows
• Administer, monitor, and manage the stability of models from a centralized view
• Optimization of the production time