Cloud Hosting

As data becomes an integral tool for transformation and differentiation for companies across various sectors and sizes, the role of the Head of Analytics/Chief Data Science Officer becomes a critical one. Earlier, analytics used to operate at a functional level. Today, in many cases, it is a strategic imperative. And it starts right with the Head of Analytics/Chief Data Officer roles.Krishna Kumar, Founder and CEO, Simplilearn, says that the skills needed for the role include communication and technical expertise. He lists four areas of focus:Technical proficiency: Strong understanding of data science and analytics techniques, including statistical analysis, data visualisation, machine learning, and data mining. Proficiency in programming languages such as Python, R, or SQL is often required Leadership and management: Ability to lead and manage a team of data scientists or analysts effectively. This includes setting goals, assigning tasks, providing guidance and fostering a collaborative and innovative work environment Strategic thinking: Capability to align data science and analytics initiatives with the organisation's overall goals and strategic vision. This involves identifying opportunities where data can drive business value and formulating data-driven strategies

Communication skills: Excellent communication skills to effectively convey complex technical concepts to both technical and non-technical stakeholders. This includes presenting insights, findings and recommendations in a clear and concise manner

Ability to weave a compelling narrative: Must be a great storyteller, be able to confidently and articulately weave a data narrative in an insightful manner that every key stakeholder, executive and senior leader will be able understand the usability of analytics teams existence or impact on mission-critical goals and business outcomes

Data governance and compliance: An understanding of data governance frameworks, privacy regulations and ethical considerations related to data handling and analysis is increasingly important. The Head of Analytics should be knowledgeable about data protection best practices and ensure compliance with relevant laws and regulations

Analytical thinking: The ability to approach complex business problems analytically, break them down into manageable components, and identify key insights and trends from large data sets. Strong critical thinking and problem-solving skills are essential

Business acumen: Understanding the organisations goals, strategy and industry landscape is essential to align analytics initiatives with business objectives. The Head of Analytics should possess the ability to translate data insights into actionable recommendations for the organisation's growth and decision-making processes. This could result in an analytics strategy and road map for analytics capabilities, prioritise initiatives, and allocate resources effectively

Continuous learning: Given the rapidly evolving field of analytics, a Head of Analytics should have a mindset of continuous learning. Staying updated with the latest advancements, industry trends and emerging technologies is crucial for keeping the analytics function relevant and effective

Kumar of Simplilearn further breaks down some of the technical skill requirements:Programming skills: Proficiency in programming languages such as Python or R, SQL are crucial for data manipulation, analysis and modelling. Strong programming skills enable you to handle large datasets, implement algorithms and automate tasks efficiently.

Statistical analysis: A solid understanding of statistical concepts and methods is essential for interpreting data, drawing meaningful conclusions and making accurate predictions. This includes knowledge of hypothesis testing, regression analysis, probability theory and experimental design.

Machine learning: Familiarity with machine learning techniques is highly valuable. This includes both supervised and unsupervised learning algorithms such as linear regression, decision trees, random forests, support vector machines, clustering and neural networks. Practical experience in applying these algorithms to real-world datasets is important.

As technology and data continue to lead front and centre in the upcoming decades, the role of the Head of Analytics/Chief Data Office will encompass multiple requirements from ethics and privacy to data and business impact.

See the original post here:

Want to become the Head of Analytics? Here are the must-have skill sets - The Economic Times

Produce (Pty) Ltd. farm in Groenfontein, South Africa, on Wednesday, Aug. 24, 2022. Photographer: Guillem Sartorio/Bloomberg 2022 Bloomberg Finance LP

Sometimes, starting fresh with custom solutions can be far more efficient than patching and updating older systems. That's why Africa's underdeveloped electrical infrastructure offers a lucrative opportunity for bitcoin miners using renewable energy and off-grid technologies.

Bitcoin miningthe process that appends transactions to the bitcoin blockchain and secures the overall networkcan offer a way to scale energy storage and demand in lockstep with growing communities. In short, it's easy to turn bitcoin mining hardware on and off to suit demand.

Despite widespread concerns about the prospect of environmental damage caused by bitcoin mining's carbon footprint, industry studies reveal that bitcoin mining may be one of the world's most sustainable tech industry sectors. For example, Q4 2022 data published by the global consortium Bitcoin Mining Council indicated that 58.9% of the global energy consumption associated with bitcoin mining comes from renewables. In my home country of Nigeria, the bitcoin industry offers unique ways to tackle urbanization issues with homegrown solutions.

These solutions are less likely to rely on legacy electrical grids than any North American counterparts. Instead, many hydropower bitcoin miners provide an always-on-demand buyer of first and last resort for energy projects in developing areas.

More than 500 million people in Africa currently lack reliable electricity access, according to the International Energy Agency. As such, one of Africa's most effective bitcoin mining strategies is to build micro grids powered by renewable energy sources in rural communities beyond the reach of main power grids.

This symbiosis between bitcoin miners and remote communities attracts hobbyists and companies that both see vast growth potential for the bitcoin industry across Africa.

Gridless Mining Facility in Kenya

Home

For example, beyond Nigeria's rural hobbyists, the Kenyan bitcoin mining company Gridless uses similar hydro-powered micro grids (under 1 megawatt capacity) to provide electricity to three rural communities in East Africa. The company raised $2 million in seed funding led by Jack Dorsey's Block and the bitcoin venture capital firm Stillmark earlier this year to expand operations to other rural communities across Kenya.

In an effort to standardize a common approach to sustainable bitcoin mining and encourage collaboration across industry players, Gridless launched the Green Africa Mining Alliance (GAMA) with three other companies, Sukuma Ventures from Kenya, Trojan Mining from Nigeria, and QRB Labs from Ethiopia. Earlier this month, they released the "Blueprint for Bitcoin Mining and Energy in Africa" report with actionable insights for "reducing the electricity-access gap in underprivileged regions" using small, custom grids and bitcoin data centers.

Although bitcoin-savvy entrepreneurs and investors see the lucrative potential for eco-friendly bitcoin mining sites across Africa, opaque regulations still present various challenges.

Many African bitcoin hobbyists and miners prefer to remain anonymous rather than join public-facing corporate ventures like GAMA for fear of government backlash. African governments have neither explicitly forbidden bitcoin mining nor offered clear bitcoin mining regulations. Therefore, some off-grid bitcoin miners see that uncertainty as not worth the risk of drawing attention to themselves.

Nonetheless, those who operate relatively large bitcoin mining operations struggle to receive energy development licenses, not to mention the high cost of importing hardware equipment for bitcoin mining. Regardless of the regulation that may arise as the bitcoin mining industry becomes a more prevalent part of African economies, it's clear that we've only scratched the surface of what is possible when African communities develop their infrastructure solutions.

On the whole, bitcoin usage beyond crypto exchange platforms remains a grassroots movement across Africa. For this reason, organizations like GAMA take a long-term approach to growth rather than merely rushing to replicate bitcoin mining models already popularized in Asia, Europe, and the Americas.

While challenges still need to be addressed and questions answered, such as regulatory requirements for bitcoin-powered companies and the steep hardware costs, Africans are already pioneering the future of sustainable bitcoin mining methods and systems.

I'm a Nigerian Bitcoin Core contributor, CEO of the Bitcoin venture capital firm Recursive Capital, as well as the co-founder of Qala, a bitcoin education program designed to train the next generation of African Bitcoin developers. I also serve as a board member of trust, a nonprofit focused on growing the Bitcoin ecosystem in Africa.

Read the original:

Africans Are Pioneering The Bright, Yet Complicated, Green Future Of Bitcoin Mining - Forbes

If the pandemic taught me anything, it was that our government is filled with short-sighted, corrupt, and inept actors who will rationalize any action, no matter how damaging it may be for the majority, in the name of safety and for alleged security. Even the terms "safety," "security," and "emergency" have been bastardized to the point of it being rhetorically flexible terminology that can be adjusted to create the most desirable outcome not for the American people but for America's governmental apparatus.

Montana's ban on TikTok is another such episode. Last week, Montana Gov. Greg Gianforte signed a bill banning TikTok in the state and from Apple and Google app stores within its bordersin the name of keeping Montana residents safe from a foreign adversary and trending degeneracy. In reality, it's a tragic example of another short-sighted governmental action that promises to be the beginning of a trend of infringing on the rights of Americans.

While the bill, known as SB 419, cites concerns over alleged surveillance from the Chinese government, it also rationalizes the ban on the grounds of what Gianforte's administration believes is TikTok's habit of encouraging "dangerous activities" among younger users, things like "throwing objects at moving automobiles" and "lighting a mirror on fire and then attempting to extinguish it using only one's body parts."

While many Republicans are applauding this surface-level effort to annoy the Chinese Communist Party, I see this landmark legislation for what it really is: a Trojan horse to normalize and rationalize internet censorship.

The "Twitter Files" repeatedly showed us how desperate departments of the U.S. government are to censor the speech of regular people under the guise of protecting the American public from "misinformation." And I don't see this action made by the state of Montana as any different.

If the government can rationalize banning a website or application to "protect" Americans from a "security danger," what else could they ban on the internet for your own security? What's to stop Democrats from framing Twitter as a security risk, because they no longer play nice with the security state behind the scenes?

While I agree that government officials or anyone in any important corporate position shouldn't be using TikTok on their phones due to the risk of espionage, there is this illusion that our data is ours, when in truth, everything we do on the internet has long been sold to marketing firms and data brokers across the world decades ago.

What's to stop the CCP from purchasing this data from a third party? Nothing. Heck, the U.S. Government does it all the time.

No one can tell you exactly what will happen if the CCP has your 18-year-old son's TikTok usage data, but we're supposed to raise hell about this while Google and Apple have been data mining millions of Americans for years.

The truth is that this ban won't be nearly as effective as they claim. There is nothing to stop someone in Montana from connecting to a VPN (Virtual Private Network) connection marked in a different state to continue to utilize the platform, which will mean that the next battle will be over the legality of VPNs or at the very least, regulating VPNs.

Their other rationalization for banning TikTok is TikTok's facilitation of idiotic behavior by young people. But perhaps unfortunately, the government can't legislate stupidity; if it could, a lot of politicians wouldn't have jobs.

Young people with not yet fully developed brains who are highly impulsive have been doing dumb and dangerous things well before the existence of social media. Just in my lifetime, I've seen the craze of backyard wrestling and the obsession over imitating the reckless behavior of MTV's Jackass; none of this is new.

Instead of involving the government in preventing our children from using TikTok, maybe more American parents need to act like parents and restrict it themselves.

Chinese Corporations, and by extension, the CCP, have invested over $190 billion between 2005 and 2022 in nearly every major industry in America, including real estate, energy, and entertainment. The Chinese have long embedded themselves into our economy, yet our government does nothing about it. But you're supposed to clutch your pearls and wish for censorship because they know what kind of makeup your daughter likes to apply?

It's time to see this for what it is: an excuse to begin a program of mass censorship. Don't be fooled, and don't support it.

Adam B. Coleman is the author of "Black Victim To Black Victor" and writer on Substack at adambcoleman.substack.com.

The views expressed in this article are the writer's own.

Visit link:

Banning TikTok Won't Protect Kids. It's the Opening to Mass Internet Censorship | Opinion - Newsweek

By Basem Khandakji |

( Middle East Monitor ) An Amnesty International report published this month revealed details of the latest systems used by the Zionist state to enhance its comprehensive monitoring of occupied Palestine and its people, who are subject to the surveillance, control and punishment of this fascist security regime. The report noted that the Israeli security services are using high-tech surveillance systems through their military checkpoints across the occupied Palestinian West Bank; the systems are called Red Wolf, Blue Wolf and Wolf Pack.

Red Wolf is the newest system and is used by the Zionist colonial troops specifically in the city of Hebron. The system works by scanning Palestinians faces as they pass through the discriminatory security checkpoints with neither their knowledge nor consent.

The Zionist states security databases must be loaded with the Palestinians biometric data, as they are the targets of the system. This is done by providing each colonial checkpoint with more than 15,000 images capable of performing face recognition on everyone who passes through or is detained there.

The Blue Wolf system is an electronic application installed by the Zionist soldiers on their smart phones, which guarantees the photographing and monitoring of all Palestinians passing through the checkpoints, including children and the elderly. This photo data helps to update the security database used by the colonial Israeli security system to persecute and pursue Palestinians.

The Wolf Pack relies primarily on the information and data provided by both the Red Wolf and Blue Wolf systems to build the largest database possible of most of the Palestinians in the occupied West Bank. In doing so, the Zionist security system uses the latest and most accurate surveillance technology in the world.

All of this demonstrates the extent of Israels obsession with turning the Palestinians into mere data and numbers. The objective is to strip away the emotions, morality and humanity of the oppressed Palestinian people, but in doing so it also removes all three from the inhuman Israeli oppressors. Stripping them of these characteristics is intended to ease the surveillance, persecution, marginalisation and confiscation process established by the Zionist colonial apartheid system. Using these electronic wolves de-humanises the Palestinians in the eyes of the oppressors and makes it easier to persecute and, when deemed necessary, kill them. This creates some distance between Israeli tyranny on the ground and the faade of the states supposedly moral stance and conscience, in a way that guarantees that the oppression and exclusion can continue.

In short, the electronic wolves act as a proxy free of consciousness, rationality or morality so that the survivors of Nazism and their descendants are not filled with guilt about pursuing the Palestinians and liquidating them. The settler-colonial state promotes this illusion of moral distance with its encyclopaedic collection of gaunt images of the persecuted Palestinian people. Unwittingly, the Zionists behind the use of this technology are actually filling their soldiers minds with subconscious reminders that they are terrorising the Palestinians.

This article first appeared in Arabic inAl-Qudson 22 May 2023 and was translated and edited for MEMO

The views expressed in this article belong to the author and do not necessarily reflect the editorial policy of Middle East Monitor or Informed Comment.

Via Middle East Monitor )

Read the rest here:

Data collected by Israel's Electronic Wolves helps to Terrorise the ... - Informed Comment

Exploring K-Means: A Comprehensive Guide to Partitioning Clustering Techniques

K-Means is a popular partitioning clustering technique that has gained significant traction in recent years, primarily due to its simplicity and effectiveness in a wide range of applications. This powerful algorithm has been employed in various fields, including data mining, machine learning, and pattern recognition, to name a few. The primary objective of K-Means is to partition a dataset into distinct clusters, where each data point belongs to the cluster with the nearest mean. This comprehensive guide aims to provide an in-depth understanding of the K-Means algorithm, its underlying principles, and its potential applications.

The K-Means algorithm is an iterative process that starts by selecting an initial set of K centroids, where K is the desired number of clusters. These centroids can be chosen randomly or based on specific criteria, such as the density of data points or their distance from one another. Once the initial centroids are selected, the algorithm proceeds to assign each data point to the nearest centroid, effectively creating K distinct clusters. Following this, the centroids are updated by calculating the mean of all data points within each cluster. This process is repeated until the centroids positions stabilize, indicating that the optimal clustering solution has been reached.

One of the key advantages of K-Means is its simplicity, which makes it easy to implement and understand. Moreover, the algorithm is highly scalable, allowing it to handle large datasets efficiently. However, K-Means also has its limitations. For instance, the algorithms performance is heavily reliant on the initial selection of centroids, which can sometimes lead to suboptimal clustering solutions. Additionally, K-Means assumes that clusters are spherical and evenly sized, which may not always be the case in real-world datasets. Despite these drawbacks, K-Means remains a popular choice for partitioning clustering tasks due to its overall effectiveness and ease of use.

One of the primary challenges associated with K-Means is determining the optimal value of K, which directly impacts the quality of the clustering solution. Various techniques have been proposed to address this issue, including the elbow method, silhouette analysis, and gap statistics. The elbow method involves plotting the sum of squared errors (SSE) for different values of K and identifying the point where the SSE starts to decrease at a slower rate. This point, resembling an elbow, represents the optimal value of K. Silhouette analysis, on the other hand, measures the similarity of data points within a cluster and their dissimilarity to data points in neighboring clusters. A high silhouette score indicates that the data points are well-clustered, and the optimal value of K can be determined by comparing the scores for different values of K. Gap statistics is another technique that compares the within-cluster dispersion for different values of K to a reference null distribution, with the optimal value of K corresponding to the largest gap.

In recent years, several variants of the K-Means algorithm have been developed to address its limitations and improve its performance. Some of these variants include K-Means++, which aims to improve the initial selection of centroids, and Binary K-Means, which is designed for clustering binary data. Additionally, researchers have proposed hybrid approaches that combine K-Means with other clustering techniques, such as hierarchical clustering and density-based clustering, to achieve better results.

In conclusion, K-Means is a powerful partitioning clustering technique that has proven to be effective in a wide range of applications. Its simplicity, scalability, and ease of implementation have made it a popular choice among researchers and practitioners alike. While the algorithm has its limitations, ongoing research and development efforts continue to improve its performance and broaden its applicability. As a result, K-Means remains an essential tool in the data scientists arsenal, offering valuable insights and solutions in the ever-evolving world of data analysis.

Go here to see the original:

K-Means: An Introduction to Partitioning Clustering - CityLife