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How Has the Pandemic Impacted Global Expansion and Talent Strategies?

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Click to learn more about author Bob Cahill.

One year ago, domestic and global business planning was thrown into confusion virtually overnight as lockdown, remote working, and a growing public health crisis took hold. Today, as vaccination programs gather pace, company leaders are taking stock and beginning to look ahead, many with growing optimism and confidence.

There are certainly grounds for positivity. The Organisation for Economic Co-operation and Development (OECD), for instance, recently updated its forecast for the U.S. economy, predicting it will grow by 6.5% this year – a considerable increase from its December 2020 estimation, which stood at 3.2%. As pointed out in an analysis by the Chief Investment Officer website, “It would be only the second time since 1966 that US GDP growth exceeded 6%, following behind 1984 when GDP growth was a red-hot 7.2%.”

Welcome as this news is, it doesn’t simply indicate a strong economic rebound to a situation where organizations return to pre-pandemic business as usual. Big questions remain: Have company leaders, for instance, become more domestically focused on their strategy, or will international growth once again rise up the list of priorities?

In the last year, much has changed and savvy industry leaders are drawing on lessons learned during lockdown to innovate around their business models. Take CFOs, for example, who perhaps more than any other group across the business landscape, have a detailed appreciation of the impact of a global pandemic and how organizations should plot a course out the other side. A useful indicator of general prosperity are the plans they make for international expansion, and my company’s recent research has revealed some fascinating findings.

The survey revealed three major illustrative trends, particularly around how talent acquisition and workforce management strategies are closely tied to growing levels of confidence among CFOs that we are now entering a robust and sustainable recovery. Specifically:

1. CFOs are taking a global view within their business strategies and hiring approaches.

CFOs have a high degree of interest in tapping into a more cost-effective, global talent pool (a concept favored by 85%) and capturing market share through global expansion (favored by 81%). By contrast, in our corresponding 2020 CFO survey, only 63% of respondents said they were moving forward with global expansion plans in the face of the COVID-19 pandemic. 

When asked to describe their hiring strategy over the next 12 to 18 months, 42% said they want to attract new talent that is unbounded by the geographic restrictions of their company’s operating model. 

2. CFOs have altered workforce management strategies.

Three-quarters of the executives also said the COVID-19 pandemic fundamentally altered the way they think about hiring and workforce management and 81% said it altered how they consider remote employees or the work-from-anywhere model. More specifically, 75% of the survey respondents anticipate operating remote or hybrid workforce models in the next 12 to 18 months. 

3. CFOs are optimistic in 2021 and believe that their success is tied to global expansion.

Ninety-three percent of the surveyed executives predicted that their companies will meet or exceed their 2021 goals and a resounding 81% are planning expansions into new countries as part of their long-term growth strategies. This near-ubiquitous level of confidence is extremely good news, especially given the huge levels of uncertainty that dominated corporate thinking throughout much of 2020.

But how will talent strategies change as a result? Clearly, the survey data points to the fact that CFOs are now recalibrating their plans in order to maximize the opportunity that global remote teams provide from a long-term business perspective, including cost efficiency and access to hard-to-find talent. In addition, the hubs for highly skilled talent are shifting and currently half of the world’s college graduates come from top emerging countries, which means that companies that adopt this strategy now will be able to gain a competitive advantage in the future.

Also, an added benefit that should be noted is that a global workforce typically provides better bottom-line results. Study after study points to the fact that employees who are part of a diverse culture are much happier and more engaged.

In Summary

Despite the challenges of the last 15 months, CFOs are putting their optimism into practice. Global expansion opportunities abound, including newly shaped post-pandemic markets and M&A opportunities. The pandemic has reshaped attitudes about remote and borderless work, and CFOs who can reimagine their business models to tap into the global talent pool will build their companies’ most important asset: their people.

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://www.dataversity.net/how-has-the-pandemic-impacted-global-expansion-and-talent-strategies/

Big Data

Analytics Engineering Everywhere

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Analytics Engineering Everywhere

Many new roles have appeared in the data world ever since the rise of the Data Scientist took the spotlight several years ago. Now, there is a new core player ready to take center stage, and we may see in five years, nearly every organization will have an Analytics Engineering team.


By Jason Ganz, a senior data analyst at GoCanvas.

Analytics Engineering — An Introduction

There’s a quiet revolution happening in the world of data. For years we have been blasted with nonstop articles about “The Sexiest Job of the 21st Century” — a data scientist. A data scientist, we have been taught, is a figure of almost otherworldly intelligence who uses quasi-mystical arts to perform feats of data wizardly. But these days, if you talk to the people who watch the data space most closely — there’s a different data role that has them even more excited.

To be clear, there are some very real and very cool applications of data science that can allow organizations to do things with data that can completely transform how their organization operates. But for many orgs, particularly smaller organizations without millions of dollars to invest, data science initiatives tend to fall flat because of the lack of a solid data infrastructure to support them.

While everyone was focused on the rise of data science, another discipline has been quietly taking shape, driven not by glitzy articles in Harvard Business Review but by the people working in the trenches in data-intensive roles. They call it the analytics engineer.

An analytics engineer is someone who brings together the data-savvy and domain knowledge of an analyst with software engineering tooling and best practices. Day to day, that means spending in a suite of tools that is becoming known as “The Modern Data Stack” and particularly dbt. These tools allow analytics engineers to centralize data and then model it for analysis in a way that is remarkably cheap and easy compared to how the ETL of traditional Business Intelligence teams of the past operated.

While data scientists are seen by some as wizardry, the attitude of the analytics engineer is a little different. You’ll hear them refer to themselves as everything from “humble data plumbers’’ to “just a pissed off data analyst.” The work of an Analytics Engineer seems easy to understand, almost banal. They combine data sources, apply logic, make sure there are clean and well-modeled materializations to analyze.

It turns out analytics engineering is a goddamn superpower. Anyone that has worked in, well, basically any organization knows that a tremendous amount of effort goes into standardizing data points that feel like they should be a no-brainer to pull, while more complex questions just sit unanswered for years. Analytics Engineering allows you to have data systems that just work.

A good analytics engineer is hugely impactful for an org, with each analytics engineer being able to help build a truly data-driven culture in ways that would be challenging for a team of people using legacy tools. While in the past there was tremendous repetitive work to do any simple analysis, Analytics Engineers can build complex data models using tools like dbt and have analysis-ready data tables built on any schedule. While before it was impossible to get anyone to agree on standard definitions of metrics, Analytics Engineers can simply build them into their codebase. And in the past, people struggled with incomplete and messy data, and Analytics Engineers… still struggle with incomplete and messy data. But at least we can have a suite of tests on our analytics systems to know when something has gone wrong!

The Rise of Analytics Engineering

You might think that this development would be scary for people working in data — if one analytics engineer is substantially more impactful than a data analyst, won’t our jobs be at risk? Could an org replace five data analysts with one Analytics Engineer and come out ahead?

But the fact of the matter is that no data analyst, anywhere, has ever come close to performing all of the analysis they think could be impactful at their organization — the opposite is far more likely to be the problem. Most data orgs are begging for additional headcount.

As analytics engineers increase the amount of insight organizations can find from data, it actually becomes more likely that these orgs will want to hire additional data talent (both analytics engineers and analysts). In his fantastic post The Reorganization of the Factory, Erik Bernhardsson makes the case that as the toolsets for software engineers has become ever more efficient, the demand for software engineers has counterintuitively grown — as there are more and more use cases where it now makes sense to build software rather than a manual process. This point not only holds for data, but I think it actually is more true for data.

While every organization needs software, not every organization needs software engineers. But every organization needs to learn from their data, and since the ways in which the data needs to be understood will be unique at every organization, they will all need analytics engineers. Software is commonly said to be eating the world — analytics engineering will be embedded in the world. As the incremental value of each data hire rises, there are substantial new areas where data insights and learnings could be applied that they aren’t today. And even if you aren’t interested in becoming an analytics engineer, having well modeled and accurate data makes data analysts and data scientists more effective. It’s a win across the board.

That does not necessarily mean that every analytics engineering role will be doing good for the world. Having more powerful data operations allows you to question, seek insights, and look for new strategies. It can also allow an organization new ways to monitor their employees, surveil, or discriminate. One needs only look at the myriad of public issues in the tech and data science industries right now to see the ways that powerful tech can be misused. It is important to recognize the potential dangers as well as the new opportunities.

If it feels like we’re at a real inflection point for Analytics Engineering — it’s because we are. What was very recently the domain of a few adventurous data teams is quickly becoming industry standard for tech organizations — and there’s every reason to think that other types of organizations will be following along shortly. The impact is just too high.

We’re about to see a huge expansion in the number of and types of places where you can find employment as an analytics engineer. The coming boom in opportunities for analytics engineers will take place across three rough domains, with each having different challenges and opportunities.

  • More and more large enterprises, both tech and non-tech organizations, are going to adapt to the modern data stack. As analytics engineering is brought into the most complex legacy data systems, we’ll begin to see what patterns develop to support analytics engineering at scale. If you are interested in really figuring out what the large-scale data systems of the future look like, this will be the place to go.
  • Just about every new company is going to be searching for an analytics engineer to lead their data initiatives. This will give them a step up against any competition that isn’t investing in their core data. Being an early analytics engineer at a fast-growing company is tremendously fun and exciting, as you are able to build up a data organization from scratch and see firsthand how analytics engineering can change the trajectory of an organization.
  • Finally, many organizations outside the tech business world are going to begin seeing the impact that analytics engineering can bring. You might not have quite the same tech budget, and you might have to learn to advocate for yourself a little more but it might be the area where analytics engineering has the most potential to do good for the world. City governments will use analytics engineering to monitor programs and ensure that government resources are being used effectively. Academic institutions will use analytics engineering to create datasets, many of them public, that will aid in scientific and technological development. The possibility space is wide open.

Analytics engineering is fundamentally a discipline that’s about making sense of the world around us. It’s about allowing everyone in an organization to see a little bit further in their impact on the org and how their work connects to it. Right now, analytics engineering is still a new discipline — pretty soon, it will be everywhere.

Original. Reposted with permission.

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Source: https://www.kdnuggets.com/2021/06/analytics-engineering-everywhere.html

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Text detection from images using EasyOCR: Hands-on guide

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EasyOCR | Text detection from images using EasyOCR: Hands-on guide





















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Source: https://www.analyticsvidhya.com/blog/2021/06/text-detection-from-images-using-easyocr-hands-on-guide/

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Why and how to use BERT for NLP Text Classification?

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Why and how to use BERT for NLP Text Classification? – Analytics Vidhya





















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Source: https://www.analyticsvidhya.com/blog/2021/06/why-and-how-to-use-bert-for-nlp-text-classification/

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As Venezuela’s economy regresses, crypto fills the gaps

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By Brian Ellsworth

CARACAS (Reuters) – Venezuelan food delivery driver Pablo Toro has no stake in cryptocurrency or blockchain, but indirectly uses digital tokens every time he sends money to his family.

Toro, who emigrated to Colombia in 2019, uses an app called Valiu to receive Colombian pesos from working on Bogota’s streets and deposit the corresponding bolivars into a Venezuelan bank account.

In Venezuela’s economy, mired by hyperinflation and hemmed in by sanctions, the operation is not so straightforward.

Valiu uses pesos to buy cryptocurrency that it then sells on LocalBitcoins, a global peer-to-peer site for trading tokens in local currencies.

For Toro, the platform is more reliable than informal money changers, the main channel for Venezuelan migrants to send money home. And he need not buy traditional money orders in person.

“When the power is out in Venezuela, when internet service is down, it has a huge impact on how long it takes to send a remittance to one’s family,” said Toro, who quit working as a university security guard because his monthly salary could not even pay for a day’s groceries.

“(Now) I don’t have to worry about whether the cell signal dropped in Venezuela, or if cell service drops here.”

As hyperinflation and U.S. sanctions disrupt Venezuela’s economy, cryptocurrency is emerging as a way to provide services handled elsewhere by the traditional banking system.

It has become a tool to send remittances, protect wages from inflation and help businesses manage cash flow in a quickly depreciating currency, according to interviews with crypto users and experts.

Cryptocurrency in Latin America got renewed attention in June after El Salvador adopted bitcoin as legal tender. It has grown in popularity in Argentina as inflation resurged.

Chainalysis, a startup that researches blockchain transactions, in a 2020 report ranked Venezuela third on its Global Crypto Adoption Index, largely due to the high volume of bolivar transactions.

Mining cryptocurrency – using high-powered computers to solve complex math problems – is an attractive way to make extra income thanks to Venezuela’s ultra-low power prices, but the average citizen cannot afford the equipment.

In Venezuela, crypto is mainly used to hedge against inflation that causes bank deposits to sharply depreciate in weeks or even days.

“Valiu buys and sells bitcoin instead of directly exchanging pesos to bolivars because of the lack of availability of that currency in regulated marketplaces,” said Alejandro Machado, Valiu’s head of pilot programs.

Bolivar transactions on LocalBitcoins are the largest by value among Latin American currencies, according to LocalBitcoins data analyzed by blockchain advisor UsefulTulips.

LocalBitcoins did not respond to a request for comment.

Cryptocurrency traders and experts say volumes on the site have slipped amid the rising popularity of Binance, one of the world’s largest cryptocurrency exchanges, which offers trading of a variety of tokens.

These include so-called “stablecoins” whose values remain steady against specific assets such as the U.S. dollar, avoiding the volatility of many cryptocurrencies.

Bolivar operations on Binance’s peer-to-peer platform have risen by 75% since May, making Venezuela the only Latin American country whose trading volumes have risen since bitcoin prices tumbled at the start of May, a Binance spokesperson said.

Venezuelan President Nicolas Maduro in 2017 announced the creation of the state-backed petro cryptocurrency, but it has little practical application. The government used it in 2019 to make small payments to retirees, and often uses it as a unit of value to price services or fines that are ultimately paid in bolivars.

The United States in 2019 imposed broad Venezuela sanctions that block U.S. citizens from dealing with Maduro’s government. While banks can still deal with private businesses or individuals, many avoid doing so due to perceived regulatory risk.

The country’s information ministry did not respond to a request for comment.

Fast food chains Pizza Hut and Church’s Chicken as well as some supermarkets are accepting tokens such as bitcoin and dash as payment, fueling excitement and filling malls and businesses with logos for well-known cryptocurrencies.

But a major part of Venezuela’s crypto operations involves businesses swapping out of bolivars to beat inflation, said economist and finance expert Aaron Olmos.

“Crypto is being used as a palliative for the economic situation, but you see it mostly among businesses,” said Olmos.

“Nobody is going to tell you ‘every night when we do the books, we convert bolivars into bitcoin,’ but yes, this is happening.”

(Reporting by Brian Ellsworth; Editing by Richard Chang)

Image Credit: Reuters

Coinsmart. Beste Bitcoin-Börse in Europa
Source: https://datafloq.com/read/as-venezuelas-economy-regresses-crypto-fills-gaps/15682

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