Giancarlo Angulo's Blog
Analysis and Opinion By Irineo B. R. Salazar The Philippines is an enigma to many. There is the “Heritage of Smallness” (Nick Joaquin) which doesn’t scale well, as I have written in “The National Village”. There is a certain insularity which I think is the result of having gone From the Edge to the Middle […]
Widening Philippine Horizons
I am in mourning. fuck
Summary Don’t be a regular user. Be a power user instead. Always go a step further than the others and see where it takes you. Always take note of inefficiencies and try to mitigate them. My solution to this should be familiar to most developers: a Kanban board. Every time I notice something that slows me down, I write it down as a To-Do. Whenever I have some time to spare, I try to find a fix for it.
But to
But to do this, philanthropists need to be cannier about their analysis and tactics. At present, most philanthropists with concerns about disadvantage tend to focus on alleviating its symptoms rather than addressing its causes. They fund projects to feed the hungry, create jobs, build housing and improve services. But all that good work can be wiped out by public spending cuts, predatory lending or exploitative low levels of pay.
And there is a deeper problem. When it comes to addressing inequality, a well intentioned philanthropist might finance educational bursaries for children from disadvantaged backgrounds, or fund training schemes to equip low-paid workers for better jobs. That allows a few people to exit bad circumstances, but it leaves countless others stuck in under-performing schools or low-paid insecure work at the bottom of the labour market. Very few concerned philanthropists think of financing research or advocacy to address why so many schools are poor or so many jobs are exploitative. Such an approach, says David Callahan of Inside Philanthropy, is like “nurturing saplings while the forest is being cleared”.
By contrast, conservative philanthropists have, in the past two decades, operated at a different level. Their agenda has been to change public debate so that it is more accommodating of their neoliberal worldview, which opposes the regulation of finance, improvements in the minimum wage, checks on polluting industries and the establishment of universal healthcare. They fund climate change-denying academics, support free-market thinktanks, strike alliances with conservative religious groups, create populist TV and radio stations, and set up “enterprise institutes” inside universities, which allows them, not the universities, to select the academics.
Research by Callahan reveals that more liberal-minded philanthropists have never understood the importance of cultivating ideas to influence key public policy debates in the way conservatives have.
Only a few top philanthropic foundations – such as Ford, Kellogg and George Soros’ Open Society Foundations – give grants to groups working to empower the poor and disadvantaged in such areas. Most philanthropists see them as too political. Many of the new generation of big givers come out of a highly entrepreneurial business world, and are disinclined to back groups that challenge how capitalism operates. They are reluctant to back groups lobbying to promote the empowerment of the disadvantaged people whom these same philanthropists declare they intend to assist. They tend not to fund initiatives to change tax and fiscal policies that are tilted in favour of the wealthy, or to strengthen regulatory oversight of the financial industry, or to change corporate culture to favour greater sharing of the fruits of prosperity. They rarely think of investing in the media, legal and academic networks of key opinion-formers in order to shift social and corporate culture and redress the influence of conservative philanthropy.
Source: How philanthropy benefits the super-rich | Philanthropy | The Guardian
Data Quality Dimensions
DQ dimensions are a common way to identify and cluster DQ checks. There are many definitions, and the number of dimensions varies considerably: You might find 16, or even more dimensions. From a practical perspective, it is less confusing to start with a few dimensions and find a general understanding of them among your users.
- Completeness: Is all the data required available and accessible? Are all sources needed available and loaded? Was data lost between stages?
- Consistency: Is there erroneous/conflicting/inconsistent data? For example, the termination date of a contract in a “Terminated” state must contain a valid date higher than or equal to the start date of the contract.
- Uniqueness: Are there any duplicates?
- Integrity: Is all data linked correctly? For example, are there orders linking to nonexistent customer IDs (a classic referential integrity problem)?
- Timeliness: Is the data current? For example, in a data warehouse with daily updates, I would expect yesterday’s data available today.
Source: Data Quality Implementation in Data Warehouses | Toptal
Once, small firms centred on inventors were responsible for most of our innovation. Larger firms might buy or exploit these steps forwards, but they did not typically make them. And then for a brief period, this changed: many of the best new products, tools, and ideas came from research labs within large corporations. This brief period also happened to be the era when scientific, technological, and economic productivity sped forward at its fastest ever clip. Yet almost as soon as it arrived, the fruitful period was over and we returned to a situation where small companies and small-business-like teams at universities developed innovations outside of large companies and sold them in a market for ideas. Though we might enjoy the innovation created by small flexible firms, we should not dismiss the contributions made by large corporate labs. The corporate lab may be creeping back, but aggressively prosecuting antitrust against large firms growing organically through in-house research could easily snuff this spark out.
Source: The rise and fall of the industrial R&D lab – Works in Progress
Choose your leaders with wisdom and forethought.
To be led by a coward is to be controlled by all that the coward fears.
To be led by a fool is to be led by the opportunists who control the fool.
To be led by a thief is to offer up your most precious treasures to be stolen.
To be led by a liar is to ask to be told lies.
To be led by a tyrant is to sell yourself and those you love into slavery.
But if this is your vision of the romance-writing world, you might have missed its evolution into a billion-dollar-a-year business. In 2016 romance made up 23 percent of the overall U.S. fiction market, and the net worth of some of its writers exceeds that of John Grisham (see Nora Roberts and Danielle Steel). According to Christine Larson, a romance expert and journalism professor at the University of Colorado Boulder, 45 percent of the romance writers she surveyed made enough to support themselves without a day job—“that is shocking for any group of writers,” she said—and thanks mainly to their embrace of digital publishing, 17 percent make more than $100,000 a year. Not Mark Zuckerberg money, but far more than the $45,000 median income of American working women.
Serverless adoption rates have been climbing ever since the technology was brought into the spotlight with the release of AWS Lambda in 2014. That is because serverless makes an offer that cloud developers simply can not resist, providing the following benefits:
- Server management is abstracted to vendor
- Pay-as-you-go model where you only pay for what you use
- Automatically scalable and highly available
These benefits are achieved by the characteristics that define the technology. Serverless applications are stateless distributed systems that scale to the needs of the system, providing event-based and async models of development. This has worked in favor of the technology, resulting in a desirable solution for the cloud.
However, does this offer always live up to what it is perceived as?
With further inspection, there is no doubt that serverless adoption also opens up developers to the possibility of falling into anti-patterns specific to the model. This is especially concerning seeing the high adoption rates of serverless. As more of the industry moves to reap the benefits, we must be wary of what works and what does not work. Serverless is definitely beneficial, however, the wrong use of it could leave a sour taste, pushing the industry away from the technology.
Therefore the purpose of this piece is to highlight the anti-patterns that plague serverless architectures and how they may be avoided. Hence enabling the success of serverless applications and also promoting its adoption.
Source: Breaking Down Serverless Anti-Patterns – DZone Cloud
In fact, the company refers to its target customers as CATS: “curious, aspiring 30-somethings.” CATS are old enough not to be planning to return to school, but young enough, in theory, that they need help advancing in their career. A CAT is a person whose life has become complicated, who has had to put aside some of the things they loved to do, who isn’t exactly doing the thing they dreamed of doing, David Schriber, MasterClass’s chief marketing officer, told me. They’re anxious about their future, their present, their position relative to that of their peers. “They’ll talk about having anxiety that their co-workers or the people on their social networks all seem to know more about a subject than they do,” Schriber said, referring, presumably, to pre-pandemic focus testing. “Someone will come to the office party and talk about wine, and then they’ll feel like I don’t know enough about wine. Someone else will talk about photography, and they’ll be like Man, I should pay attention to who the photographers are these days. Or their boss will say things like ‘You need to work on your leadership profile, or hone your creative judgments,’ and the poor 30-something is like Where am I gonna get all this?” Something about this struck me as clammy and sad, as far away from They can’t take your education away from you as it’s possible to be. As though it’s revealing another layer of unpaid labor—cultural labor—one is expected to do in order to secure the privilege of performing actual labor.
Source: Can MasterClass Really Teach You to Serve Like Serena Williams? – The Atlantic