JavaScript client API for Google Apps Script API primerBruce McPherson
An API for JavaScript/jQuery client webapps providing CRUD access to Google Apps Script scriptDB - a free noSQL databases. This adds to a VBA API for Excel already published. Now Excel, Google Apps Script and JavaScript clients can share the same noSQL database and data.
JavaScript client API for Google Apps Script API primerBruce McPherson
An API for JavaScript/jQuery client webapps providing CRUD access to Google Apps Script scriptDB - a free noSQL databases. This adds to a VBA API for Excel already published. Now Excel, Google Apps Script and JavaScript clients can share the same noSQL database and data.
Do something in 5 with gas 4- Get your analytics profiles to a spreadsheetBruce McPherson
Another in the 'do something useful with Google Apps Script' series. This time you'll see how to use the Analytics service and use exponential backoff to mitigate for quota rate limiting.
Do something in 5 minutes with gas 1-use spreadsheet as databaseBruce McPherson
Here's one in a series of tutorials where you can do something useful from scratch in 5 minutes using Google Apps Script. This example shows how to use a Google Spreadsheet as a database
Taming the beast - how to tame React & GraphQL, one error at a timeSusanna Wong
Though there are multiple tutorials on GraphQL and React online, there are not much sharing of trivial mistakes that beginners need to take care of, which dives deep into the understanding of how the library works behind the scenes. This presentation is a lightening talk and an attempt to share the first two errors that I encountered in my journey in learning about React and GraphQL.
Demostración del paso a paso para conectarse a los datos de una lista de SharePoint utilizando llamadas a la API desde una WebPart de SharePoint Framework, realizando las tareas de Creación, Actualización, Eliminación y Consulta de Datos.
Using Reason's type inference we can create GraphQL servers with 100% type coverage. Regardless if we compile to Node.js or native binaries using Reason we can do this with ease.
Besides that Reason shines even more so on the client. Send one quick introspection request and you get full auto completion on your schema right in the browser.
Why using composition in React ? What are the alternative (mixins, inheritance)? How to use composition to build your React application? What are the pros and cons?
Article on Corporate Social Responsibility - an insightFCS BHAVIK GALA
India is the first country in the world to have a regulatory framework for CSR by law. The Companies Act, 2013 has introduced the idea of CSR to the forefront and through its disclose-or-explain mandate, is promoting greater transparency and disclosure. Schedule VII of the Act, which lists out the CSR activities, suggests communities to be the focal point. On the other hand, by discussing a company’s relationship to its stakeholders and integrating CSR into its core operations, the rules suggest that CSR needs to go beyond communities and beyond the concept of philanthropy.This Article provides insight to the regulatory aspects of CSR in India
Painting the inside or the outside of a house may be quite an arduous task, however, few understand that adding a recent splash of color to the walls and siding of their homes will cause reduced energy consumption and substantial savings on utility bills. Seal Coatings Thermal Solutions, LLC, of Melbourne, Florida, is manufacturing a really complicated mix of a ceramic vacuum-filled refractory product designed to attenuate the trail of hot air transfer through ceilings, walls, and roofs. The insulating ceramic technology blocks the transfer of warmth outward once applied to color on interior walls and ceilings and prevents the transfer of warmth inward once accustomed paint exterior walls and roofs, effectively providing year-around comfort within the home.
Do something in 5 with gas 4- Get your analytics profiles to a spreadsheetBruce McPherson
Another in the 'do something useful with Google Apps Script' series. This time you'll see how to use the Analytics service and use exponential backoff to mitigate for quota rate limiting.
Do something in 5 minutes with gas 1-use spreadsheet as databaseBruce McPherson
Here's one in a series of tutorials where you can do something useful from scratch in 5 minutes using Google Apps Script. This example shows how to use a Google Spreadsheet as a database
Taming the beast - how to tame React & GraphQL, one error at a timeSusanna Wong
Though there are multiple tutorials on GraphQL and React online, there are not much sharing of trivial mistakes that beginners need to take care of, which dives deep into the understanding of how the library works behind the scenes. This presentation is a lightening talk and an attempt to share the first two errors that I encountered in my journey in learning about React and GraphQL.
Demostración del paso a paso para conectarse a los datos de una lista de SharePoint utilizando llamadas a la API desde una WebPart de SharePoint Framework, realizando las tareas de Creación, Actualización, Eliminación y Consulta de Datos.
Using Reason's type inference we can create GraphQL servers with 100% type coverage. Regardless if we compile to Node.js or native binaries using Reason we can do this with ease.
Besides that Reason shines even more so on the client. Send one quick introspection request and you get full auto completion on your schema right in the browser.
Why using composition in React ? What are the alternative (mixins, inheritance)? How to use composition to build your React application? What are the pros and cons?
Article on Corporate Social Responsibility - an insightFCS BHAVIK GALA
India is the first country in the world to have a regulatory framework for CSR by law. The Companies Act, 2013 has introduced the idea of CSR to the forefront and through its disclose-or-explain mandate, is promoting greater transparency and disclosure. Schedule VII of the Act, which lists out the CSR activities, suggests communities to be the focal point. On the other hand, by discussing a company’s relationship to its stakeholders and integrating CSR into its core operations, the rules suggest that CSR needs to go beyond communities and beyond the concept of philanthropy.This Article provides insight to the regulatory aspects of CSR in India
Painting the inside or the outside of a house may be quite an arduous task, however, few understand that adding a recent splash of color to the walls and siding of their homes will cause reduced energy consumption and substantial savings on utility bills. Seal Coatings Thermal Solutions, LLC, of Melbourne, Florida, is manufacturing a really complicated mix of a ceramic vacuum-filled refractory product designed to attenuate the trail of hot air transfer through ceilings, walls, and roofs. The insulating ceramic technology blocks the transfer of warmth outward once applied to color on interior walls and ceilings and prevents the transfer of warmth inward once accustomed paint exterior walls and roofs, effectively providing year-around comfort within the home.
its about a major scam happened in India in recent years.. Its called " 2G SCAM " .
I created a ppt on it in my school days... and i want to spread the same knowledge to everyone out there..
My name is Maysoon Zayid,and I am not drunk,but the doctor who delivered me was.He cut my mom six different times in six different directions,suffocating poor little me in the process.As a result,I have cerebral palsy,which means I shake all the time. Look. It's exhausting.I'm like Shakira,Shakira meets Muhammad Ali.CP is not genetic.It's not a birth defect.You can't catch it.No one put a curse on my mother's uterus,and I didn't get it because my parents are first cousins,which they are.It only happens from accidents,like what happened to me on my birthday.
CAMBRIDGE AS HISTORY: ALL ABOUT THE BOER WARS. It contains: origins of the Boer Wars, the Great Trek, Transvaal and Orange Free State, the Confederation of South African States, the First Boer War, the Second Boer War.
Vice President of Sales and Marketing Available!!!Jeff Pickett
Good marketing efforts work in all industries!!! Hard work and dedication to product positioning are cornerstones to success. When you find someone who gets it, try to bring them on board.
Well, I am here and ready to go for your team!!!
ggtimeseries-->ggplot2 extensions
This R package offers novel time series visualisations. It is based on ggplot2 and offers geoms and pre-packaged functions for easily creating any of the offered charts. Some examples are listed below.
This package can be installed from github by installing devtools library and then running the following command - devtools::install_github('Ather-Energy/ggTimeSeries').
reference: https://github.com/Ather-Energy/ggTimeSeries
User Defined Aggregation in Apache Spark: A Love StoryDatabricks
Defining customized scalable aggregation logic is one of Apache Spark’s most powerful features. User Defined Aggregate Functions (UDAF) are a flexible mechanism for extending both Spark data frames and Structured Streaming with new functionality ranging from specialized summary techniques to building blocks for exploratory data analysis.
Attached here is a presentation that I made covering some bits and pieces of what I got to discover about Data Science and Machine Learning using R Programming Language.
“Practical Data Science”. R programming language and Jupiter notebooks are used in this tutorial. However, the concepts are generic and can be applied for Python or other programming language users as well.
R is a language and environment for statistical computing and graphics. R is free, this slide is for beginner. start from the basic first. variables, data structure, reading data, chart, function, conditional statement, iteration, grouping, reshape, string operations.
This is a brief introduction to how R can be useful in the manufacturing sector to calculate the frequency of faults and then developing the model so that preventive maintenance can be done
Apache Spark for Library Developers with William Benton and Erik ErlandsonDatabricks
As a developer, data engineer, or data scientist, you’ve seen how Apache Spark is expressive enough to let you solve problems elegantly and efficient enough to let you scale out to handle more data. However, if you’re solving the same problems again and again, you probably want to capture and distribute your solutions so that you can focus on new problems and so other people can reuse and remix them: you want to develop a library that extends Spark.
You faced a learning curve when you first started using Spark, and you’ll face a different learning curve as you start to develop reusable abstractions atop Spark. In this talk, two experienced Spark library developers will give you the background and context you’ll need to turn your code into a library that you can share with the world. We’ll cover: Issues to consider when developing parallel algorithms with Spark, Designing generic, robust functions that operate on data frames and datasets, Extending data frames with user-defined functions (UDFs) and user-defined aggregates (UDAFs), Best practices around caching and broadcasting, and why these are especially important for library developers, Integrating with ML pipelines, Exposing key functionality in both Python and Scala, and How to test, build, and publish your library for the community.
We’ll back up our advice with concrete examples from real packages built atop Spark. You’ll leave this talk informed and inspired to take your Spark proficiency to the next level and develop and publish an awesome library of your own.
Covid19py by Konstantinos Kamaropoulos
A tiny Python package for easy access to up-to-date Coronavirus (COVID-19, SARS-CoV-2) cases data.
ref:https://github.com/Kamaropoulos/COVID19Py
https://pypi.org/project/COVID19Py/?fbclid=IwAR0zFKe_1Y6Nm0ak1n0W1ucFZcVT4VBWEP4LOFHJP-DgoL32kx3JCCxkGLQ
"optrees" package in R and examples.(optrees:finds optimal trees in weighted ...Dr. Volkan OBAN
Finds optimal trees in weighted graphs. In
particular, this package provides solving tools for minimum cost spanning
tree problems, minimum cost arborescence problems, shortest path tree
problems and minimum cut tree problem.
by Volkan OBAN
k-means Clustering in Python
scikit-learn--Machine Learning in Python
from sklearn.cluster import KMeans
k-means clustering is a method of vector quantization, originally from signal processing, that is popular for cluster analysis in data mining. k-means clustering aims to partition n observations into k clusters in which each observation belongs to the cluster with the nearest mean, serving as a prototype of the cluster. This results in a partitioning of the data space into Voronoi cells.
The problem is computationally difficult (NP-hard); however, there are efficient heuristic algorithms that are commonly employed and converge quickly to a local optimum. These are usually similar to the expectation-maximization algorithm for mixtures of Gaussian distributions via an iterative refinement approach employed by both algorithms. Additionally, they both use cluster centers to model the data; however, k-means clustering tends to find clusters of comparable spatial extent, while the expectation-maximization mechanism allows clusters to have different shapes.[wikipedia]
ref: http://scikit-learn.org/stable/auto_examples/cluster/plot_cluster_iris.html
Forecasting through ARIMA Modeling using R
ref:http://ucanalytics.com/blogs/step-by-step-graphic-guide-to-forecasting-through-arima-modeling-in-r-manufacturing-case-study-example/
k-means Clustering and Custergram with R.
K Means Clustering is an unsupervised learning algorithm that tries to cluster data based on their similarity. Unsupervised learning means that there is no outcome to be predicted, and the algorithm just tries to find patterns in the data. In k means clustering, we have the specify the number of clusters we want the data to be grouped into. The algorithm randomly assigns each observation to a cluster, and finds the centroid of each cluster.
ref:https://www.r-bloggers.com/k-means-clustering-in-r/
ref:https://rpubs.com/FelipeRego/K-Means-Clustering
ref:https://www.r-bloggers.com/clustergram-visualization-and-diagnostics-for-cluster-analysis-r-code/
Data Science and its Relationship to Big Data and Data-Driven Decision MakingDr. Volkan OBAN
Data Science and its Relationship to Big Data and Data-Driven Decision Making
To cite this article:
Foster Provost and Tom Fawcett. Big Data. February 2013, 1(1): 51-59. doi:10.1089/big.2013.1508.
Foster Provost and Tom Fawcett
Published in Volume: 1 Issue 1: February 13, 2013
ref:http://online.liebertpub.com/doi/full/10.1089/big.2013.1508
https://www.researchgate.net/publication/256439081_Data_Science_and_Its_Relationship_to_Big_Data_and_Data-Driven_Decision_Making
R Machine Learning packages( generally used)
prepared by Volkan OBAN
reference:
https://github.com/josephmisiti/awesome-machine-learning#r-general-purpose
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Empowering the Data Analytics Ecosystem: A Laser Focus on Value
The data analytics ecosystem thrives when every component functions at its peak, unlocking the true potential of data. Here's a laser focus on key areas for an empowered ecosystem:
1. Democratize Access, Not Data:
Granular Access Controls: Provide users with self-service tools tailored to their specific needs, preventing data overload and misuse.
Data Catalogs: Implement robust data catalogs for easy discovery and understanding of available data sources.
2. Foster Collaboration with Clear Roles:
Data Mesh Architecture: Break down data silos by creating a distributed data ownership model with clear ownership and responsibilities.
Collaborative Workspaces: Utilize interactive platforms where data scientists, analysts, and domain experts can work seamlessly together.
3. Leverage Advanced Analytics Strategically:
AI-powered Automation: Automate repetitive tasks like data cleaning and feature engineering, freeing up data talent for higher-level analysis.
Right-Tool Selection: Strategically choose the most effective advanced analytics techniques (e.g., AI, ML) based on specific business problems.
4. Prioritize Data Quality with Automation:
Automated Data Validation: Implement automated data quality checks to identify and rectify errors at the source, minimizing downstream issues.
Data Lineage Tracking: Track the flow of data throughout the ecosystem, ensuring transparency and facilitating root cause analysis for errors.
5. Cultivate a Data-Driven Mindset:
Metrics-Driven Performance Management: Align KPIs and performance metrics with data-driven insights to ensure actionable decision making.
Data Storytelling Workshops: Equip stakeholders with the skills to translate complex data findings into compelling narratives that drive action.
Benefits of a Precise Ecosystem:
Sharpened Focus: Precise access and clear roles ensure everyone works with the most relevant data, maximizing efficiency.
Actionable Insights: Strategic analytics and automated quality checks lead to more reliable and actionable data insights.
Continuous Improvement: Data-driven performance management fosters a culture of learning and continuous improvement.
Sustainable Growth: Empowered by data, organizations can make informed decisions to drive sustainable growth and innovation.
By focusing on these precise actions, organizations can create an empowered data analytics ecosystem that delivers real value by driving data-driven decisions and maximizing the return on their data investment.
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”