Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.
Data Scientist vs Data Analyst vs Data Engineer - Role & Responsibility, Skil...Simplilearn
In this presentation, we will decode the basic differences between data scientist, data analyst and data engineer, based on the roles and responsibilities, skill sets required, salary and the companies hiring them. Although all these three professions belong to the Data Science industry and deal with data, there are some differences that separate them. Every person who is aspiring to be a data professional needs to understand these three career options to select the right one for themselves. Now, let us get started and demystify the difference between these three professions.
We will distinguish these three professions using the parameters mentioned below:
1. Job description
2. Skillset
3. Salary
4. Roles and responsibilities
5. Companies hiring
This Master’s Program provides training in the skills required to become a certified data scientist. You’ll learn the most in-demand technologies such as Data Science on R, SAS, Python, Big Data on Hadoop and implement concepts such as data exploration, regression models, hypothesis testing, Hadoop, and Spark.
Why be a Data Scientist?
Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data scientist you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
Simplilearn's Data Scientist Master’s Program will help you master skills and tools like Statistics, Hypothesis testing, Clustering, Decision trees, Linear and Logistic regression, R Studio, Data Visualization, Regression models, Hadoop, Spark, PROC SQL, SAS Macros, Statistical procedures, tools and analytics, and many more. The courseware also covers a capstone project which encompasses all the key aspects from data extraction, cleaning, visualisation to model building and tuning. These skills will help you prepare for the role of a Data Scientist.
Who should take this course?
The data science role requires the perfect amalgam of experience, data science knowledge, and using the correct tools and technologies. It is a good career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Data Scientist Master’s Program, including:
IT professionals
Analytics Managers
Business Analysts
Banking and Finance professionals
Marketing Managers
Supply Chain Network Managers
Those new to the data analytics domain
Students in UG/ PG Analytics Programs
Learn more at https://www.simplilearn.com/big-data-and-analytics/senior-data-scientist-masters-program-training
Agile & Data Modeling – How Can They Work Together?DATAVERSITY
A tenet of the Agile Manifesto is ‘Working software over comprehensive documentation’, and many have interpreted that to mean that data models are not necessary in the agile development environment. Others have seen the value of data models for achieving the other core tenets of ‘Customer Collaboration’ and ‘Responding to Change’.
This webinar will discuss how data models are being effectively used in today’s Agile development environment and the benefits that are being achieved from this approach.
RFM stands for Recency, Frequency, and Monetary value, each corresponding to some key customer trait. These RFM metrics are important indicators of a customer’s behavior because frequency and monetary value affects a customer’s lifetime value, and recency affects retention, a measure of engagement.
RFM analysis helps marketers find answers to the following questions:
Who are your best customers?
Which of your customers could contribute to your churn rate?
Who has the potential to become valuable customers?
Which of your customers can be retained?
Which of your customers are most likely to respond to engagement campaigns?
Let's find out more with the help of Slideshare.
Dave Kellogg presentation to a high-growth SaaS company's All Hands meeting / speaker series in February, 2019. Discusses the key elements of making a great SaaS company, but quantitative and qualitative.
Basic Concepts of Business Data Analytics, Evolution of Business Analytics, Data Analytics, Business Data Analytics Applications, Scope of Business Analytics.
Understanding your audience and considering them in your design is essential for building great visualizations. This deck will walk you through the critical steps for identifying and understanding your audience, and developing a complex visualization storyboard to share your message.
Data Scientist vs Data Analyst vs Data Engineer - Role & Responsibility, Skil...Simplilearn
In this presentation, we will decode the basic differences between data scientist, data analyst and data engineer, based on the roles and responsibilities, skill sets required, salary and the companies hiring them. Although all these three professions belong to the Data Science industry and deal with data, there are some differences that separate them. Every person who is aspiring to be a data professional needs to understand these three career options to select the right one for themselves. Now, let us get started and demystify the difference between these three professions.
We will distinguish these three professions using the parameters mentioned below:
1. Job description
2. Skillset
3. Salary
4. Roles and responsibilities
5. Companies hiring
This Master’s Program provides training in the skills required to become a certified data scientist. You’ll learn the most in-demand technologies such as Data Science on R, SAS, Python, Big Data on Hadoop and implement concepts such as data exploration, regression models, hypothesis testing, Hadoop, and Spark.
Why be a Data Scientist?
Data scientist is the pinnacle rank in an analytics organization. Glassdoor has ranked data scientist first in the 25 Best Jobs for 2016, and good data scientists are scarce and in great demand. As a data scientist you will be required to understand the business problem, design the analysis, collect and format the required data, apply algorithms or techniques using the correct tools, and finally make recommendations backed by data.
Simplilearn's Data Scientist Master’s Program will help you master skills and tools like Statistics, Hypothesis testing, Clustering, Decision trees, Linear and Logistic regression, R Studio, Data Visualization, Regression models, Hadoop, Spark, PROC SQL, SAS Macros, Statistical procedures, tools and analytics, and many more. The courseware also covers a capstone project which encompasses all the key aspects from data extraction, cleaning, visualisation to model building and tuning. These skills will help you prepare for the role of a Data Scientist.
Who should take this course?
The data science role requires the perfect amalgam of experience, data science knowledge, and using the correct tools and technologies. It is a good career choice for both new and experienced professionals. Aspiring professionals of any educational background with an analytical frame of mind are most suited to pursue the Data Scientist Master’s Program, including:
IT professionals
Analytics Managers
Business Analysts
Banking and Finance professionals
Marketing Managers
Supply Chain Network Managers
Those new to the data analytics domain
Students in UG/ PG Analytics Programs
Learn more at https://www.simplilearn.com/big-data-and-analytics/senior-data-scientist-masters-program-training
Agile & Data Modeling – How Can They Work Together?DATAVERSITY
A tenet of the Agile Manifesto is ‘Working software over comprehensive documentation’, and many have interpreted that to mean that data models are not necessary in the agile development environment. Others have seen the value of data models for achieving the other core tenets of ‘Customer Collaboration’ and ‘Responding to Change’.
This webinar will discuss how data models are being effectively used in today’s Agile development environment and the benefits that are being achieved from this approach.
RFM stands for Recency, Frequency, and Monetary value, each corresponding to some key customer trait. These RFM metrics are important indicators of a customer’s behavior because frequency and monetary value affects a customer’s lifetime value, and recency affects retention, a measure of engagement.
RFM analysis helps marketers find answers to the following questions:
Who are your best customers?
Which of your customers could contribute to your churn rate?
Who has the potential to become valuable customers?
Which of your customers can be retained?
Which of your customers are most likely to respond to engagement campaigns?
Let's find out more with the help of Slideshare.
Dave Kellogg presentation to a high-growth SaaS company's All Hands meeting / speaker series in February, 2019. Discusses the key elements of making a great SaaS company, but quantitative and qualitative.
Basic Concepts of Business Data Analytics, Evolution of Business Analytics, Data Analytics, Business Data Analytics Applications, Scope of Business Analytics.
Presentation delivered by David Bloch at AWS Executive day in Auckland, New Zealand. Covering the things that must be true to make Data a Strategic Asset
Stripe pitch deck designed by Zlides
Want to create a pitch deck that inspires your audience? Get your FREE presentation kit designed by Zlides: http://bit.ly/slideshare_zlides
"Using Data to Set Product Strategy" by Justin BauerProductized
The way businesses are being built is shifting right before our eyes. Whole industries are being disrupted in real time and those that are able to take advantage are reaping massive returns.
In this PRODUCTIZED talk, Justin Bauer, VP of Product at Amplitude, shares his advice from working with dozens of the world’s fastest growing companies on how to:
- Create clarity using a clear and measurable north star metric
- Integrate behavioral science into their decision making frameworks to build deep user empathy
- Rapidly iterate to drive systematic and efficient growth
Building the Billion dollar SaaS Unicorn for 2018Kelly Schwedland
In a Venture Capital world that is obsessed with growth, recurring revenue and software as a service, after you validate that you have a solution that people are willing to pay for, there is an entire new world ahead of you in scaling that venture. For many, this involves an entirely new language and set of metrics to manage the business. For the startup that wants to make the leap to scale up and fast growth this should serve as a starting point for key insights and metrics for that journey.
"Building Sales Operations from $1M to $50M: Who to hire, when and why"saastr
SaaStr Annual 2017
Matt Cameron (Fmr. WW Head of Corporate Sales & VP of Sales at Kahuna) and Volney Spalding (VP Sales Operations, xMatters) talk about hiring stage-appropriate sales teams and scaling Sales Ops.
Coping and Leading the Change Rapid and breathtaking technology advances are forcing radical changes in how IT delivers serviced, the Service Desk supports these services and the business utilizes these services. "If you don't like change, you'll like irrelevance even less" stated four-star US General (Ret.) Eric Shineski reflecting on the consequences of not embracing change. This session explores the impact of rapidly changing technology and business trends on the Service Desk strategy, structure, services, processes, tools and most importantly – the Service Desk professionals. In coping with this accelerated change, Service Desk leaders must take action now. McGarahan will share lessons learned from Service Desks who are incorporating practices in supporting mobility, social knowledge, multi-generational and cultural customers, virtual and cloud computing and the change in service level expectations. Please join Peter McGarahan he relates insights into:
• The urgent and undeniable need for Service Desk leaders to assess their current strategy, structure, services and skills against the current realities of business and technology advances.
• Recent game-changing developments, including virtual and cloud computing (hosted services and software solutions) mobile computing, strategic sourcing, and remote / virtual workers.
• The resulting impact in designing services with the customer top-of-mind, delivering resolution closest to the customer and knowledge at the ‘speed of conversation’ by integrating best practices with the tools, people, and existing processes.
This slide gives an excellent overview of Agile Planning and Estimation.
Will be really helpful, if presented to a Scrum/Agile Team to understand activities related to Release Planning, Sprint Planning and Estimation
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
Business Value Metrics for Data GovernanceDATAVERSITY
As data professionals, we recognize and understand the need for data governance, focusing on data quality in particular. We have made progress in this area, as illustrated by the emergence of the Chief Data Officer role in recent years. However, in many organizations, the need for governance is still largely unrecognized, and remains very tough to sell internally. You may need some detailed information and metrics to demonstrate the business value. This session will focus on business justification for establishing a data governance framework, including:
Data classification
Data quality
Business value metrics (KPIs)
Presentation delivered by David Bloch at AWS Executive day in Auckland, New Zealand. Covering the things that must be true to make Data a Strategic Asset
Stripe pitch deck designed by Zlides
Want to create a pitch deck that inspires your audience? Get your FREE presentation kit designed by Zlides: http://bit.ly/slideshare_zlides
"Using Data to Set Product Strategy" by Justin BauerProductized
The way businesses are being built is shifting right before our eyes. Whole industries are being disrupted in real time and those that are able to take advantage are reaping massive returns.
In this PRODUCTIZED talk, Justin Bauer, VP of Product at Amplitude, shares his advice from working with dozens of the world’s fastest growing companies on how to:
- Create clarity using a clear and measurable north star metric
- Integrate behavioral science into their decision making frameworks to build deep user empathy
- Rapidly iterate to drive systematic and efficient growth
Building the Billion dollar SaaS Unicorn for 2018Kelly Schwedland
In a Venture Capital world that is obsessed with growth, recurring revenue and software as a service, after you validate that you have a solution that people are willing to pay for, there is an entire new world ahead of you in scaling that venture. For many, this involves an entirely new language and set of metrics to manage the business. For the startup that wants to make the leap to scale up and fast growth this should serve as a starting point for key insights and metrics for that journey.
"Building Sales Operations from $1M to $50M: Who to hire, when and why"saastr
SaaStr Annual 2017
Matt Cameron (Fmr. WW Head of Corporate Sales & VP of Sales at Kahuna) and Volney Spalding (VP Sales Operations, xMatters) talk about hiring stage-appropriate sales teams and scaling Sales Ops.
Coping and Leading the Change Rapid and breathtaking technology advances are forcing radical changes in how IT delivers serviced, the Service Desk supports these services and the business utilizes these services. "If you don't like change, you'll like irrelevance even less" stated four-star US General (Ret.) Eric Shineski reflecting on the consequences of not embracing change. This session explores the impact of rapidly changing technology and business trends on the Service Desk strategy, structure, services, processes, tools and most importantly – the Service Desk professionals. In coping with this accelerated change, Service Desk leaders must take action now. McGarahan will share lessons learned from Service Desks who are incorporating practices in supporting mobility, social knowledge, multi-generational and cultural customers, virtual and cloud computing and the change in service level expectations. Please join Peter McGarahan he relates insights into:
• The urgent and undeniable need for Service Desk leaders to assess their current strategy, structure, services and skills against the current realities of business and technology advances.
• Recent game-changing developments, including virtual and cloud computing (hosted services and software solutions) mobile computing, strategic sourcing, and remote / virtual workers.
• The resulting impact in designing services with the customer top-of-mind, delivering resolution closest to the customer and knowledge at the ‘speed of conversation’ by integrating best practices with the tools, people, and existing processes.
This slide gives an excellent overview of Agile Planning and Estimation.
Will be really helpful, if presented to a Scrum/Agile Team to understand activities related to Release Planning, Sprint Planning and Estimation
Data Governance Best Practices, Assessments, and RoadmapsDATAVERSITY
When starting or evaluating the present state of your Data Governance program, it is important to focus on best practices such that you don’t take a ready, fire, aim approach. Best practices need to be practical and doable to be selected for your organization, and the program must be at risk if the best practice is not achieved.
Join Bob Seiner for an important webinar focused on industry best practice around standing up formal Data Governance. Learn how to assess your organization against the practices and deliver an effective roadmap based on the results of conducting the assessment.
In this webinar, Bob will focus on:
- Criteria to select the appropriate best practices for your organization
- How to define the best practices for ultimate impact
- Assessing against selected best practices
- Focusing the recommendations on program success
- Delivering a roadmap for your Data Governance program
Business Value Metrics for Data GovernanceDATAVERSITY
As data professionals, we recognize and understand the need for data governance, focusing on data quality in particular. We have made progress in this area, as illustrated by the emergence of the Chief Data Officer role in recent years. However, in many organizations, the need for governance is still largely unrecognized, and remains very tough to sell internally. You may need some detailed information and metrics to demonstrate the business value. This session will focus on business justification for establishing a data governance framework, including:
Data classification
Data quality
Business value metrics (KPIs)
The first part of this presentation is a situational assessment of typical challenges in IT project delivery using the SCRAP (Situation, Complication, Resolution, Action, Proof) model. This is essentially a business case for Agile. So if you are looking for ways to get buy-in for Agile, this is the place to be.
The second part of this presentation shows you what Agile is from 50,000 ft. From this high up, we'll be covering the essential elements from a business and management perspective. We'll cover what Agile is, what it does, how it works and what it achieves.
If you are interested in learning or communicating the value of Agile, then this is the presentation for you!
Please email me if you would like a download.
Current Trends in Agile - opening keynote for Agile Israel 2014Yuval Yeret
Yuval Yeret, AgileSparks’s CTO will give trends overview session – What is hot, what is not, in the lean agile industry/community – with the aim of exposing people and giving a big picture view that places the different trends as well as sessions in the conference into the right context. We will discuss trends like Scaling Agile (SAFe, Less, DAD), DevOps / Continuous Delivery, Modern Management aspects, Modern Change Management approaches such as Open-Agile-Adoption, What is going on in the world of Kanban, Agile Fluency, Technical Safety / Anzeneering, and maybe more.
http://agileisrael2014.com/current-trends-in-agile/
Introducing Agile Development in Traditional Software Development Organizationsjuliannacole
Highlights of actions taken to during the 2006/2007 introduction of Agile development techniques to Tribune Interactive's software development and business stakeholders.
Lean Business Analysis and UX Runway: Managing Value by Reducing Waste (Natal...IT Arena
Lviv IT Arena is a conference specially designed for programmers, designers, developers, top managers, inverstors, entrepreneur and startuppers. Annually it takes place on 2-4 of October in Lviv at the Arena Lviv stadium. In 2015 conference gathered more than 1400 participants and over 100 speakers from companies like Facebook. FitBit, Mail.ru, HP, Epson and IBM. More details about conference at itarene.lviv.ua.
Lean Business Analysis and UX Runway - Natalie WarnertNatalie Warnert
How to integrate BAs and UX in a Agile/Lean environment to create an MVP to learn while reducing potential waste. Presented at Lviv IT Arena, 2015 in Lviv, Ukraine by Natalie Warnert, October 3, 2015
www.nataliewarnert.com
ICONIQ Analytics: The Modern Developer Technology StackChristine Edmonds
Earlier this year, ICONIQ Growth¹ performed an in-depth study of the developer technology stack to help us better understanding emerging trends, most commonly adopted tools, and key questions assessed during decision making processes.
Agile is a very popular project management method. It is especially useful in managing rapid deployment of new product features in measured cycles. SharePoint 2013 can be leveraged as a platform for managing Agile
General introduction to agile practices like Scrum and Kanban. Also covers what situations Agile is best at, what situations Agile doesn't help with, and what an Agile team should look like. This deck is a general intro to Agile for OpenSource Connections clients.
For projects like building a power plant or a train tunnel, tough project managers are needed. But when it comes to developing digital or physical products, the role of a project manager has an increasingly difficult standing. During agile or digital transformations, new roles emerge to take over project management tasks. So, are project managers needed in these areas in the future?
My talk from Digital Elite Day 2020 (Conversion Elite track).
I go over the main changes in browser tracking protections since as early as 2003 (Safari version 1). Then I discuss the impact these tracking protections have on digital analytics, advertising, and experimentation.
Server-side Tagging in Google Tag Manager - MeasureSummit 2020Simo Ahava
My presentation from MeasureSummit 2020.
I walk you through the key benefits and concerns of Server-side Tagging in Google Tag Manager, before wrapping up with an example of how SST lets you reduce client-side bloat.
For more details about Server-side Tagging, see this resource: https://www.simoahava.com/analytics/server-side-tagging-google-tag-manager/
My presentation titled "Browsers eat data quality for breakfast" from SuperWeek 2020.
The presentation introduces the "tracking protection / prevention / blocking" mechanisms implemented in the major browsers.
The information comes from the www.cookiestatus.com service.
You can't spell MEASURE without CUSTOMIZATIONSimo Ahava
My presentation from the Superweek 2019 conference.
In the presentation, I discuss how critical healthy communication structures are in any project. I talk about customization and how customization can be used to overcome problems that emerge from broken communication structures AND how customization can be used to actually fix relationships and break down silos in any company.
Essential Search Marketing Tweaks For Google Analytics And Google Tag ManagerSimo Ahava
Slides from my SMX Munich 2018 talk.
How to measure engagement with the web analytics tools at our disposal?
How to turn reports more meaningful for our particular organizational idiosyncracies and goals?
How to become more critical about the data that is spoon-fed to us by the default installations of our favorite tools?
Google Tag Manager - 5 years. What have we learned?Simo Ahava
Looking back on five years of Google Tag Manager. Has the tool changed? Have we? What's coming up in the next 5 years?
My talk at MeasureCamp #11 (London).
MeasureCamp IX (London) - 10 JavaScript Concepts for web analystsSimo Ahava
Here's my list of 10 JavaScript (related) concepts that I think all web analysts should understand at least on a basic level. A solid grasp of JavaScript is a base requirement for anyone working with the web browser.
Search Marketer's Toolkit for Google Tag Manager and Google AnalyticsSimo Ahava
My slides from the Searchlove Boston conference in May 2016. The presentation covers actionable tips and tricks for working with Google Tag Manager and Google Analytics.
Content Analytics - The Whys And Hows For Google AnalyticsSimo Ahava
These are my slides from SMX München 2016. Content engagement is a tricky thing to measure, especially how it changes over time, but in this article I give some ideas for how to enhance your content measurement process within your organization.
SuperWeek 2016 - Garbage In Garbage Out: Data Quality in a TMS WorldSimo Ahava
Slides from my talk at the SuperWeek analytics conference. The focus was on organization transformation necessary to improve data quality, especially when using a tag management solution like Google Tag Manager.
Meaningful Data - Reaktor Breakpoint 2015Simo Ahava
Slides from my talk at Reaktor Breakpoint 2015 in Helsinki, Finland. The topic is Meaningful Data, and I use content engagement as an example of how to utilize Google Analytics reports to provide amazing insights with just a little customization.
Meaningful Data - Best Internet Conference 2015 (Lithuania)Simo Ahava
Here are the slides from my talk titled "Meaningful Data", which I presented at the Best Internet Conference in Vilnius, Lithuania.
I share some of my favorite Google Analytics / Google Tag Manager tweaks, along with a healthy dose of criticism towards the default configuration of our favorite analytics platforms (a phenomenon I call Plug-and-play Analytics).
Slides from my talk at MeasureCamp VII (London) in September 2015. Some key findings about Data Layers and how they are integrated with tag management solutions and organisations.
Tricks and tweaks for Google Analytics and Google Tag ManagerSimo Ahava
Slides from my talk at Google Analytics User Conference in Amsterdam.
Some preaching about data collection and then a list of my favorite ways to make GTM and GA data more meaningful to your organization and your unique business goals.
Key Insights From Funnels - Enhanced Ecommerce For Google AnalyticsSimo Ahava
The slides from my talk at GPeC Summit, Romania, on 11 May 2015.
I introduce the Enhanced Ecommerce reports for Google Analytics, but before I do, I outline my ideology for using Enhanced Ecommerce. It's not just a flashy set of reports, it's an optimization tool and a hypothesis machine. I'm less interested in successful transactions and more in things like abandonment and lack of engagement. Enhanced Ecommerce lets us expand the somewhat broken concept of a session-based conversion rate, and granularly investigate its components and particles. This way we can analyze not only transactions, visits, and visitors, but the products themselves, too.
Content Engagement with Google Analytics (Emerce Conversion 2015)Simo Ahava
My slides from the Emerce Conversion 2015 conference. Here's a nice method of reconfiguring a data collection platform such as Google Analytics so it gives you best possible data for YOUR business alone.
Enhanced Ecommerce For Content (SMX München 2015)Simo Ahava
The slides from my second talk at SMX München (18 March 2015).
I've used Enhanced Ecommerce, implemented via Google Tag Manager, to analyze the content and user funnels on my website, and how people interact with different pieces of content.
In these slides, I explain the methodology and the reasoning for such an unconventional approach.
It's such a fun experiment, but it also leads to a lot of new insights for content optimization.
Be Critical: Going Beyond The Defaults With GA And GTM (SMX Munich 2015)Simo Ahava
Slides from my first talk at SMX München on March 17, 2015. The talk was about inspiring a critical approach to the metrics and dimensions we access through tools like Google Analytics. Sometimes we have to tweak the data collection mechanism to get more relevant results in our tools. In fact, I want to say that the quality of data in these platforms is directly proportional to your understanding of how the data is collected and aggregated.
So be critical! Make the most of the metrics and dimensions, and ensure that the data you're using to grow your business is relevant.
My slides from MeasureCamp VI. I gave a talk about the most common misconceptions and preconceptions surrounding tag management and, more generally, measuring the stateless web. Most of the examples are using Google Tag Manager, but many of them should be generic enough to extend to other solutions and platforms as well.
APNIC Foundation, presented by Ellisha Heppner at the PNG DNS Forum 2024APNIC
Ellisha Heppner, Grant Management Lead, presented an update on APNIC Foundation to the PNG DNS Forum held from 6 to 10 May, 2024 in Port Moresby, Papua New Guinea.
Italy Agriculture Equipment Market Outlook to 2027harveenkaur52
Agriculture and Animal Care
Ken Research has an expertise in Agriculture and Animal Care sector and offer vast collection of information related to all major aspects such as Agriculture equipment, Crop Protection, Seed, Agriculture Chemical, Fertilizers, Protected Cultivators, Palm Oil, Hybrid Seed, Animal Feed additives and many more.
Our continuous study and findings in agriculture sector provide better insights to companies dealing with related product and services, government and agriculture associations, researchers and students to well understand the present and expected scenario.
Our Animal care category provides solutions on Animal Healthcare and related products and services, including, animal feed additives, vaccination
Bridging the Digital Gap Brad Spiegel Macon, GA Initiative.pptxBrad Spiegel Macon GA
Brad Spiegel Macon GA’s journey exemplifies the profound impact that one individual can have on their community. Through his unwavering dedication to digital inclusion, he’s not only bridging the gap in Macon but also setting an example for others to follow.
This 7-second Brain Wave Ritual Attracts Money To You.!nirahealhty
Discover the power of a simple 7-second brain wave ritual that can attract wealth and abundance into your life. By tapping into specific brain frequencies, this technique helps you manifest financial success effortlessly. Ready to transform your financial future? Try this powerful ritual and start attracting money today!
Meet up Milano 14 _ Axpo Italia_ Migration from Mule3 (On-prem) to.pdfFlorence Consulting
Quattordicesimo Meetup di Milano, tenutosi a Milano il 23 Maggio 2024 dalle ore 17:00 alle ore 18:30 in presenza e da remoto.
Abbiamo parlato di come Axpo Italia S.p.A. ha ridotto il technical debt migrando le proprie APIs da Mule 3.9 a Mule 4.4 passando anche da on-premises a CloudHub 1.0.
3. Simo Ahava
Senior Data Advocate, Reaktor
Google Developer Expert, Google Analytics
Blogger, developer, www.simoahava.com
Twitter-er, @SimoAhava
Google+:er, +SimoAhava
4. Individuals and interactions over processes and tools
Working software over comprehensive documentation
Customer collaboration over contract negotiation
Responding to change over following a plan
That is, while there is value in the items on
the right, we value the items on the left more.
Manifesto for Agile Software Development
(http://agilemanifesto.org/)
5. Agile works in analytics because it promotes
reaction over sticking to plans
6. Agile works in analytics because it promotes
multi-disciplinary teams over silos
Business design
Software
development
AnalyticsCRO UX
7. Agile works in analytics because it promotes
increments over massive releases
Sprint 1 Sprint 2 Sprint 3 Sprint 4
Contact form Server-side validation
Item1
Item2
Item3
Item4
Auto-complete
8. Agile works in analytics because it promotes
feedback loops over tunnel vision
Sprint 1 Sprint 2 Sprint 3 Sprint 4
Contact form Server-side validation
Item1
Item2
Item3
Item4
Auto-complete Inline validation
A/B test, UX and peer reviews, heatmaps, session recordings
9. Data is the lifeblood of the organization. It flows through
all departments, across job titles, permeating the very
fabric of the organization, reinforcing its foundations for
growth. It cannot and should not be contained in one
vector (a dedicated analyst) alone.
Reaktor Blog: 10 Truths About Data
(https://goo.gl/r6pdXB)
11. Idea #1: Collaboration
Daily meetings
- A call / stand-up meeting with all
team members
- Discuss key metrics via dashboard
next to the board
- Discuss if there are questions about
analytics implementation for tasks
being worked on
- Avoid "peeking" at experiments that
are on-going and making radical,
unplanned changes to data collection
12. Idea #1: Collaboration
Sprint planning
- Choose stories for the upcoming
sprint
- Discuss whether it’s important to
measure these with analytics tools
- Discuss if it’s necessary to start A/B
tests, etc.
- Choose stories based on potential
value
13. Idea #1: Collaboration
Backlog grooming
- Split / evaluate stories waiting in
the backlog
- Discuss what the Definition of
Success is for these stories
- Discuss how to measure the success
of these stories
- Discuss what the potential value of
each story is
14. Idea #1: Collaboration
Weekly / demo
- Show what’s been done so far
(and is ready for shipping)
- Discuss on-going experiments and
data collection
- Show previous test / data collection
results via a dashboard and/or
prepared presentation
- Discuss organization-wide about the
role of data in the current project
15. Idea #2: Definition of Done
Definition of Done
1. Test coverage extended to cover
the feature
2. Feature documented (only when
necessary)
3. Feature passes code/UX/peer
review
16. Idea #2: Definition of Done
- The Definition of Done is a (living)
list of items that each developed
feature must pass for the sprint to be
deemed successful
- Adding "analytics" to the DoD is a
great way to put measurement to
top-of-mind when developing
features
- It’s important to shape it into "is
discussed" rather than "is done",
because not all features can/should
be measured or tested
Definition of Done
1. Test coverage extended to cover
the feature
2. Feature documented (only when
necessary)
3. Feature passes code/UX/peer
review
4.Feature measurement / testing is
discussed
17. Idea #3: Multi-disciplinary teams
IT
UX
Data
Biz
Marketing
The Project
WORST: Lack of involvement, lack of participation, lack of collaboration, lack of trust.
18. Idea #3: Multi-disciplinary teams
IT
UX
Data
Biz
Marketing
The Project
BETTER: Good communication, lack of shared goals, lack of involvement.
19. Idea #3: Multi-disciplinary teams
The Project
BEST: Transparency, involvement, shared knowledge and skills, constant learning.
20. Idea #3: Multi-disciplinary teams
Any organization that designs a
system (defined broadly) will
produce a design whose structure
is a copy of the organization's
communication structure.
- (Mel) Conway’s law
21. A good consultant should work in a manner that
inevitably makes them redundant.
https://goo.gl/aPvVjb
22. Idea #4: Hire to educate, not to delegate
The Project
BAD: Experts are hired as extra pairs of hands and as reporting tools.
23. Idea #4: Hire to educate, not to delegate
The Project
BEST: Experts work with the team, teaching, facilitating, building processes.
24. A feature is completed when it is done successfully.
https://www.simoahava.com/analytics/definition-of-success/