Y Combinator 創業者 Paul Graham からのスタートアップへのアドバイス(スタートアップが迷った時に読む Paul Graham から...Takaaki Umada
スタートアップが迷った時に読む Paul Graham からのアドバイス集です。これまでのエッセイをトピック別にまとめ、アドバイスを抽出しました。
Y Combinator のプログラムを通して、数百社のスタートアップに対して アドバイスを続け、Y Combinator が他アクセラレーターとは別格のスタートアップを続々と輩出してこれたのは、おそらく Paul Graham のスタートアップへのアドバイスが的確だったからだろう、と思っています。なので日本でも Paul Graham のエッセイにアクセスしやすくなれば、スタートアップの皆さんの架空の相談先の一つとして役立つのではないか、と思いまとめた次第です。
併読して役立つであろうスタンフォード大学の How to Start a Startup のサマリーは以下においています。
http://www.slideshare.net/takaumada/how-to-start-a-startup-42996994
リーンアナリティクスの概要を30分で理解できるようスライドを作成しています。実際に社内プレゼンでは30分で終わりました。
リーンアナリティクスの前提となるリーンスタートアップについても簡単に説明しているため、前提知識がない人でも一通り理解できると思います。
なにかご不明の点があれば、以下までご連絡ください。
info@sikmi.com
You can get an overview of LEAN ANALYTICS in 30 minutes. Actually the in-house presentation was the end in 30 minutes.
Due to the brief description of THE LEAN STARTUP that is the premise of LEAN ANALYTICS , and I think that it can be understood one way in humans there is no prerequisite knowledge .
If there is any questions something , please contact the following .
Brand Restart 2023: Michal Orsava a Karel Juřička - Personalizace v komunikac...Taste
Jak maximalizovat užitek videoreklamy pomocí nových inovativních nástrojů? S novou technologií real-time personalizace reklamního obsahu se otevírají dveře novým cestám komunikace značky se zákazníky. Způsob, jak zautomatizovat a zefektivnit reklamu, prezentujeme na skutečných klientech a představíme výsledky.
Y Combinator 創業者 Paul Graham からのスタートアップへのアドバイス(スタートアップが迷った時に読む Paul Graham から...Takaaki Umada
スタートアップが迷った時に読む Paul Graham からのアドバイス集です。これまでのエッセイをトピック別にまとめ、アドバイスを抽出しました。
Y Combinator のプログラムを通して、数百社のスタートアップに対して アドバイスを続け、Y Combinator が他アクセラレーターとは別格のスタートアップを続々と輩出してこれたのは、おそらく Paul Graham のスタートアップへのアドバイスが的確だったからだろう、と思っています。なので日本でも Paul Graham のエッセイにアクセスしやすくなれば、スタートアップの皆さんの架空の相談先の一つとして役立つのではないか、と思いまとめた次第です。
併読して役立つであろうスタンフォード大学の How to Start a Startup のサマリーは以下においています。
http://www.slideshare.net/takaumada/how-to-start-a-startup-42996994
リーンアナリティクスの概要を30分で理解できるようスライドを作成しています。実際に社内プレゼンでは30分で終わりました。
リーンアナリティクスの前提となるリーンスタートアップについても簡単に説明しているため、前提知識がない人でも一通り理解できると思います。
なにかご不明の点があれば、以下までご連絡ください。
info@sikmi.com
You can get an overview of LEAN ANALYTICS in 30 minutes. Actually the in-house presentation was the end in 30 minutes.
Due to the brief description of THE LEAN STARTUP that is the premise of LEAN ANALYTICS , and I think that it can be understood one way in humans there is no prerequisite knowledge .
If there is any questions something , please contact the following .
Brand Restart 2023: Michal Orsava a Karel Juřička - Personalizace v komunikac...Taste
Jak maximalizovat užitek videoreklamy pomocí nových inovativních nástrojů? S novou technologií real-time personalizace reklamního obsahu se otevírají dveře novým cestám komunikace značky se zákazníky. Způsob, jak zautomatizovat a zefektivnit reklamu, prezentujeme na skutečných klientech a představíme výsledky.
How to Optimize Your LinkedIn Presence to Generate New BusinessSamantha Russell
LinkedIn is a powerful networking and lead generation tool.
In fact, according to Hubspot, LinkedIn is 277% more effective at generating leads compared to other social media platforms. In this presentation, learn how to boost your marketing strategy and your social presence with this incredible platform.
Y Combinator 風の3分ピッチテンプレートです。初期のスタートアップには以下の構成をお勧めしています。
1. Problem
2. Solution
3. Market Size
4. Traction
5. Unique Insight
6. Business Model
7. Team
UTokyo 500k 用のテンプレートとして作成しました。
フォーカスするためには、たぶんどうやってフォーカスするか(前回)に加えて、何にフォーカスするかを決める必要があって、今回は後者、つまり「フォーカスポイントを決める」方の話です。
スタートアップの初期は Y Combinator 的に言うところの Do things that don’t scale (スケールしないことをしよう)をはじめとした明確なフォーカスポイントがあると思います。ただ次第に自分たちでフォーカスポイントを決めなければいけなくなってきて、そのときにどのようにフォーカス先を意思決定すれば良いのか、どうすれば良い意思決定ができるのか、という問いが出てきて、その際に方法論の必要性が生じます。
そこで意思決定の方法論を検討するのですが、スタートアップのような情報不足や資源の制約下では、ゲーム理論をはじめとしたいわゆる規範的な normative 意思決定理論よりは、行動経済学や認知心理学の記述的な descriptive 意思決定からのアプローチが良いのかなと思い、Kahneman をはじめとした行動経済学の研究成果をベースにしています。
How to Optimize Your LinkedIn Presence to Generate New BusinessSamantha Russell
LinkedIn is a powerful networking and lead generation tool.
In fact, according to Hubspot, LinkedIn is 277% more effective at generating leads compared to other social media platforms. In this presentation, learn how to boost your marketing strategy and your social presence with this incredible platform.
Y Combinator 風の3分ピッチテンプレートです。初期のスタートアップには以下の構成をお勧めしています。
1. Problem
2. Solution
3. Market Size
4. Traction
5. Unique Insight
6. Business Model
7. Team
UTokyo 500k 用のテンプレートとして作成しました。
フォーカスするためには、たぶんどうやってフォーカスするか(前回)に加えて、何にフォーカスするかを決める必要があって、今回は後者、つまり「フォーカスポイントを決める」方の話です。
スタートアップの初期は Y Combinator 的に言うところの Do things that don’t scale (スケールしないことをしよう)をはじめとした明確なフォーカスポイントがあると思います。ただ次第に自分たちでフォーカスポイントを決めなければいけなくなってきて、そのときにどのようにフォーカス先を意思決定すれば良いのか、どうすれば良い意思決定ができるのか、という問いが出てきて、その際に方法論の必要性が生じます。
そこで意思決定の方法論を検討するのですが、スタートアップのような情報不足や資源の制約下では、ゲーム理論をはじめとしたいわゆる規範的な normative 意思決定理論よりは、行動経済学や認知心理学の記述的な descriptive 意思決定からのアプローチが良いのかなと思い、Kahneman をはじめとした行動経済学の研究成果をベースにしています。
解讀雲端大數據新趨勢
2018-05-16 @ iThome Cloud Summit 2018
雲端運算、大數據、物聯網、人工智慧,這些熱門話題從 2008 年開始就陸續出現在媒體版面上。放眼過去十年 Apache Hadoop 技術在臺灣本土的應用,本次分享將為各位解讀這四個話題之間的關聯,並探討 Big Data Stack on the Cloud 背後的市場需求驅動力,最後分享 Big Data Stack on Kubernetes 的進展。
時間:2018-02-10 台灣資料工程協會 2018 第一季技術工作坊
講題:使用普羅米修斯打造全棧式監控與告警平台
Building Full Stack Monitor and Notification with Prometheus
身為管理混合式雲端基礎建設的維運人員,面對分散在不同監控平台的數據是否感到頭疼呢?身為開發者,您是否苦於欠缺歷史監控數據來除錯或排查程式效能問題呢?本次分享將從動機面開始說明為何需要全棧式監控與告警平台,接著介紹過去一季講者如何使用普羅米修斯(Prometheus)與 Grafana 針對網路層、實體機器、虛擬機器、容器、中介軟體層(Ex. Apache Cassandra、Apache Kafka、CNCF Fluentd)、應用程式層來建立資料串流(Data Pipeline)的監控儀表板。礙於無法展示真實公司的環境,本分享將使用 Docker Compose 進行全棧式監控與告警平台的概念,也藉此逐一介紹搭建全棧式監控與告警平台會用到哪些普羅米修斯(Prometheus)的各類資料蒐集器(Exporter)。
As a Hybrid Cloud Operator, are you tired of collecting monitor metrics from different monitor services? As a Developer, do you need historical application and infrastructure metrics to debug or improve application performance? In this talk, I'll first talk about why should we build Full Stack Monitor and Notification with Prometheus and Grafana. I'll share my personal experience about monitoring network devices, physical machines, virtual machines, docker containers, Middleware (Ex. Apache Cassandra, Apapche Kafka, CNCF Fluentd) and Application metrics. I'll demonstrate an End-to-End Data Pipeline Dashboard with Docker Compose examples and introduce different kinds of Prometheus Exporter used for different monitor targets.
<b>Blending Hadoop and MongoDB with Pentaho </b>[11:10 am - 11:30 am]<br />For eCommerce companies, knowing how promoted wish-lists can spark consumer spending is an analytics goldmine. In this lightning talk, Bo Borland will demonstrate how Pentaho analytics can blend click-stream data about promoted wish-lists with sales transaction records using Hadoop, MongoDB and Pentaho to reveal patterns in online shopping behavior. Regardless of your industry or specific use model, come to this session to learn how to blend MongoDB data with any data source for greater business insight. Pentaho offers the first end-to-end analytic solution for MongoDB. From data ingestion to pixel perfect reporting and ad hoc “slice and dice” analysis, the solution meets today’s growing demand for a 360-degree view of your business.
How To Run A Successful BI Project with HadoopMammoth Data
A more in depth explanation of Business Intelligence and why being data driven is an asset. Also a quick examination of what Hadoop is and what it can do.
Collaborative Data UX Design - Virtually and Phyically Datentreiber
Many data products fail, partly because users do not understand or accept the software. To avoid this, analytics solutions e.g. KPI dashboards should be designed together with the users and this is especially true for the user interface.
At the Data Brain Meetup Datentreiber Martin Szugat showed three wireframing tools to sketch UI designs collaboratively with the users:
1) the virtual collaboration tool Miro,
2) the PowerPoint add-on PowerMockup and
3) the physical Dashboard Wireframing Kit.
Data Preparation vs. Inline Data Wrangling in Data Science and Machine LearningKai Wähner
Comparison of Data Preparation vs. Data Wrangling Programming Languages, Frameworks and Tools in Machine Learning / Deep Learning Projects.
A key task to create appropriate analytic models in machine learning or deep learning is the integration and preparation of data sets from various sources like files, databases, big data storages, sensors or social networks. This step can take up to 80% of the whole project.
This session compares different alternative techniques to prepare data, including extract-transform-load (ETL) batch processing (like Talend, Pentaho), streaming analytics ingestion (like Apache Storm, Flink, Apex, TIBCO StreamBase, IBM Streams, Software AG Apama), and data wrangling (DataWrangler, Trifacta) within visual analytics. Various options and their trade-offs are shown in live demos using different advanced analytics technologies and open source frameworks such as R, Python, Apache Hadoop, Spark, KNIME or RapidMiner. The session also discusses how this is related to visual analytics tools (like TIBCO Spotfire), and best practices for how the data scientist and business user should work together to build good analytic models.
Key takeaways for the audience:
- Learn various options for preparing data sets to build analytic models
- Understand the pros and cons and the targeted persona for each option
- See different technologies and open source frameworks for data preparation
- Understand the relation to visual analytics and streaming analytics, and how these concepts are actually leveraged to build the analytic model after data preparation
Video Recording / Screencast of this Slide Deck: https://youtu.be/2MR5UynQocs
Tableau Conference 2018: Binging on Data - Enabling Analytics at NetflixBlake Irvine
In this conference session we share how we are using Tableau “out of the box” and also describe how it fits into our overall data environment. In addition, we’ll describe how we expect to use the Data Catalog and Object Model, our explorations of large-scale data stores, and challenges we are working on including governance and data lineage. Video of session can be viewed here: https://youtu.be/Nr24tw3dmZQ
Pentaho - Jake Cornelius - Hadoop World 2010Cloudera, Inc.
Putting Analytics in Big Data Analytics
Jake Cornelius
Director of Product Management, Pentaho Corporation
Learn more @ http://www.cloudera.com/hadoop/
Clouds are Not Free: Guide to Observability-Driven Efficiency OptimizationsScyllaDB
Over the recent decade, cloud computing and cloud-native platforms emerged and promised lower costs, less effort, and more flexibility. Unfortunately, in practice, it is not so easy. Knowledge short gaps, pitfalls, the complexity of using cloud APIs, and misunderstanding of services and systems cause companies to lose millions of dollars every year. On top of that, the big data world demands more and more software and computing power every day.
Fortunately, there is a method to that madness! No matter if you build your own software, or use open-source or paid systems, there are many efficiency gains that will save tons of money. Sometimes it’s a code optimization, sometimes algorithm adjustment, sometimes system-level operation!
In this talk Bartek, an open-source maintainer of observability projects like Prometheus and Thanos, author of the “Efficient Go” book and the CNCF TAG Observability Tech Lead, will explain how to notice and uncover efficiency problems effectively thanks to the power of modern cloud-native observability and tooling. The audience will learn pragmatic practices they can do to ensure effective and sustainable optimizations and how to avoid regressions in the future. All to increase the business operational margin and enable more opportunities with more efficient software and systems.
Funnel Analysis with Apache Spark and DruidDatabricks
Every day, millions of advertising campaigns are happening around the world.
As campaign owners, measuring the ongoing campaign effectiveness (e.g “how many distinct users saw my online ad VS how many distinct users saw my online ad, clicked it and purchased my product?”) is super important.
However, this task (often referred to as “funnel analysis”) is not an easy task, especially if the chronological order of events matters.
One way to mitigate this challenge is combining Apache Druid and Apache DataSketches, to provide fast analytics on large volumes of data.
However, while that combination can answer some of these questions, it still can’t answer the question “how many distinct users viewed the brand’s homepage FIRST and THEN viewed product X page?”
In this talk, we will discuss how we combine Spark, Druid and DataSketches to answer such questions at scale.
BI congres 2014-5: from BI to big data - Jan Aertsen - PentahoBICC Thomas More
7de BI congres van het BICC-Thomas More: 3 april 2014
Reisverslag van Business Intelligence naar Big Data
De reisbranche is sterk in beweging. Deze presentatie zal een reis door klassieke en moderne BI bestemmingen zijn, toont een serie snapshots van verschillende use cases in de reisbranche. Tijdens de sessie benadrukken we de capaciteit en flexibiliteit die een BI-tool nodig heeft om u te begeleiden op uw reis van klassieke BI-implementaties naar de moderne big data uitdagingen .
Behind the Scenes at Coolblue - Feb 2017Pat Hermens
In this talk, Pat stepped us through how we integrate with the #elasticstack here at Coolblue, using tooling like #Log4Net, #Serilog, #Seq and #Redis. Along the way, we were introduced to the role of each of these technologies, and as an added bonus, Pat demo'd how we can set some of these tools up in Docker containers in order to aid our rapid development and testing feedback cycles.
Exploring Career Paths in Cybersecurity for Technical CommunicatorsBen Woelk, CISSP, CPTC
Brief overview of career options in cybersecurity for technical communicators. Includes discussion of my career path, certification options, NICE and NIST resources.
NIDM (National Institute Of Digital Marketing) Bangalore Is One Of The Leading & best Digital Marketing Institute In Bangalore, India And We Have Brand Value For The Quality Of Education Which We Provide.
www.nidmindia.com
Want to move your career forward? Looking to build your leadership skills while helping others learn, grow, and improve their skills? Seeking someone who can guide you in achieving these goals?
You can accomplish this through a mentoring partnership. Learn more about the PMISSC Mentoring Program, where you’ll discover the incredible benefits of becoming a mentor or mentee. This program is designed to foster professional growth, enhance skills, and build a strong network within the project management community. Whether you're looking to share your expertise or seeking guidance to advance your career, the PMI Mentoring Program offers valuable opportunities for personal and professional development.
Watch this to learn:
* Overview of the PMISSC Mentoring Program: Mission, vision, and objectives.
* Benefits for Volunteer Mentors: Professional development, networking, personal satisfaction, and recognition.
* Advantages for Mentees: Career advancement, skill development, networking, and confidence building.
* Program Structure and Expectations: Mentor-mentee matching process, program phases, and time commitment.
* Success Stories and Testimonials: Inspiring examples from past participants.
* How to Get Involved: Steps to participate and resources available for support throughout the program.
Learn how you can make a difference in the project management community and take the next step in your professional journey.
About Hector Del Castillo
Hector is VP of Professional Development at the PMI Silver Spring Chapter, and CEO of Bold PM. He's a mid-market growth product executive and changemaker. He works with mid-market product-driven software executives to solve their biggest growth problems. He scales product growth, optimizes ops and builds loyal customers. He has reduced customer churn 33%, and boosted sales 47% for clients. He makes a significant impact by building and launching world-changing AI-powered products. If you're looking for an engaging and inspiring speaker to spark creativity and innovation within your organization, set up an appointment to discuss your specific needs and identify a suitable topic to inspire your audience at your next corporate conference, symposium, executive summit, or planning retreat.
About PMI Silver Spring Chapter
We are a branch of the Project Management Institute. We offer a platform for project management professionals in Silver Spring, MD, and the DC/Baltimore metro area. Monthly meetings facilitate networking, knowledge sharing, and professional development. For event details, visit pmissc.org.
1. My Journey of “Innovation”
( aka “From Zero to One” )
1
Jazz Yao-Tsung Wang
Associate Researcher, NCHC
AVP, Product Management, Etu
Data Architect, TenMax
Initiator and Chair, TDEA
Shared at 2018-04-26 < >
2. Hello!
I am Jazz Wang
Co-Founder of Hadoop.TW
Initiator and Chair of Taiwan Data Engineering Association (TDEA)
Hadoop Evangelist since 2008.
Open Source Promoter. System Admin (Ops).
- 11 years (2002/08 ~ 2014/02) Associate Researcher in HPC field.
- 2 years (2014/03 ~ 2016/04) Assistant Vice President (AVP),
Product Management of ‘Big Data Platform Management’
- 2 years (2016/04 ~ Now) Data Architect of Real-Time Bidding
You can find me at @jazzwang_tw or
https://fb.com/groups/dataengineering.tw
https://slideshare.net/jazzwang
2
77. ▷ Let’s play with data together!!
○ for multiple data related communities
○ Self-organized Sustainable
○ Venue Rental for Meetups and Conference
○ Value-Added Tax (VAT) for Annual Conference
○ Financial assistance to travel
▷ 2017-07-11
77
2015 ~ 2016 2017
Transform
Data
Into
Value
83. 17
▷ (2001~2008)
○ Learn by Doing & Design Thinking
○ Value Chain & Sustainable Economy
○ Be Brave
▷ (2009~2014)
○ From Research Lab to Pilot Service
○ Platform Economy
▷ (2010~Now)
○ Crowdsourcing
▷ (2011~Now)
○
“We” not just “Me” … Create platform for young talents
▷ (2014~2016)
○ Business Canvas Value Proposition
▷ (2016~Now)
○ DevOps, SRE, Full Stack Monitoring and Notification
▷ (2017~Now)
○ Taiwan Data Engineering Association
83