Data Science with Python

| March 7, 2018

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Esri's CTO for ArcGIS Enterprise Jay Theodore and ArcGIS API for Python Lead Developer Rohit Singh discuss and demonstrate Analytics across the ArcGIS platform, within the context of Data Science. Rohit shows how the Jupyter Notebook experience is a desired experience for various data science workflows, including identifying SAM (surface to air missile) sites using deep learning techniques.

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CB4

We strive to build revolutionary yet simple solutions that empower retail teams with prescriptive analytics, powered by AI and Machine learning. Our solutions allow retailers to better understand and serve their customers. By applying patented machine learning algorithms on simple sales data, CB4’s software solution captures lost sales by correcting operational inefficiencies on a SKU at store level.

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Data Analytics vs Data Science Comparison

Article | March 17, 2020

The terms data science and data analytics are not unfamiliar with individuals who function within the technology field. Indeed, these two terms seem the same and most people use them as synonyms for each other. However, a large proportion of individuals are not aware that there is actually a difference between data science and data analytics.It is pertinent that individuals whose work revolves around these terms or the information and technology industries, should know how to use these terms in the appropriate contexts. The reason for this is quite simple: the right usage of these terms has significant impacts on the management and productivity of a business, especially in today’s rapidly data-dependent world.

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MiPasa project and IBM Blockchain team on open data platform to support Covid-19 response

Article | March 17, 2020

Powerful technologies and expertise can help provide better data and help people better understand their situation. As the world contends with the ongoing coronavirus outbreak, officials battling the pandemic need tools and valid information at scale to help foster a greater sense of security for the public. As technologists, we have been heartened by the prevalence of projects such as Call for Code, hackathons and other attempts by our colleagues to rapidly create tools that might be able to help stem the crisis. But for these tools to work, they need data from sources they can validate. For example, reopening the world’s economy will likely require not only testing millions of people, but also being able to map who tested positive, where people can and can’t go and who is at exceptionally high risk of exposure and must be quarantined again.

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Straight to the Top: Why Incorta Beats Top Cloud Vendors in Dresner Advisory’s 2020 Market Study

Article | March 17, 2020

Business agility is the name of the game in 2020. Last year, the US-China trade wars gave business leaders around the world a preview of what it looks like when change and uncertainty become the new normal in the global economy—and for those caught flatfooted, it wasn’t pretty. Here we are nearly one year later and the world has changed dramatically once again. The trade war fiasco? That was just a dress rehearsal compared to what we are living through today with the recent outbreak of COVID-19. At times like these, few things matter more than having visibility into and the freedom to innovate with data to address the necessary business agility.

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Will Quantum Computers Make Supercomputers Obsolete in the Field of High Performance Computing?

Article | March 17, 2020

If you want an explicit answer without having to know the extra details, then here it is: Yes, there is a possibility that quantum computers can replace supercomputers in the field of high performance computing, under certain conditions. Now, if you want to know how and why this scenario is a possibility and what those conditions are, I’d encourage you to peruse the rest of this article. To start, we will run through some very simple definitions. Definitions If you work in the IT sector, you probably would have heard of the terms ‘high performance computing’, ‘supercomputers’ and ‘quantum computers’ many times. These words are thrown around quite often nowadays, especially in the area of data science and artificial intelligence. Perhaps you would have deduced their meanings from their context of use, but you may not have gotten the opportunity to explicitly sit down and do the required research on what they are and why they are used. Therefore, it is a good idea to go through their definitions, so that you have a better understanding of each concept. High Performance Computing: It is the process of carrying out complex calculations and computations on data at a very high speed. It is much faster than regular computing. Supercomputer: It is a type of computer that is used to efficiently perform powerful and quick computations. Quantum Computing: It is a type of computer that makes use of quantum mechanics’ concepts like entanglement and superposition, in order to carry out powerful computations. Now that you’ve gotten the gist of these concepts, let’s dive in a little more to get a wider scope of how they are implemented throughout the world. Background High performance computing is a thriving area in the sector of information technology, and rightly so, due to the rapid surge in the amount of data that is produced, stored, and processed every second. Over the last few decades, data has become increasingly significant to large corporations, small businesses, and individuals, as a result of its tremendous potential in their growth and profit. By properly analysing data, it is possible to make beneficial predictions and determine optimal strategies. The challenge is that there are huge amounts of data being generated every day. If traditional computers are used to manage and compute all of this data, the outcome would take an irrationally long time to be produced. Massive amounts of resources like time, computational power, and expenses would also be required in order to effectuate such computations. Supercomputers were therefore introduced into the field of technology to tackle this issue. These computers facilitate the computation of huge quantities of data at much higher speeds than a regular computer. They are a great investment for businesses that require data to be processed often and in large amounts at a time. The main advantage of supercomputers is that they can do what regular computers need to do, but much more quickly and efficiently. They have an overall high level of performance. Till date, they have been applied in the following domains: • Nuclear Weapon Design • Cryptography • Medical Diagnosis • Weather Forecasting • Online Gaming • Study of Subatomic Particles • Tackling the COVID-19 Pandemic Quantum computers, on the other hand, use a completely different principle when functioning. Unlike regular computers that use bits as the smallest units of data, quantum computers generate and manipulate ‘qubits’ or ‘quantum bits’, which are subatomic particles like electrons or photons. These qubits have two interesting quantum properties which allow them to powerfully compute data – • Superposition: Qubits, like regular computer bits, can be in a state of 1 or 0. However, they also have the ability to be in both states of 1 and 0 simultaneously. This combined state allows quantum computers to calculate a large number of possible outcomes, all at once. When the final outcome is determined, the qubits fall back into a state of either 1 or 0. This property iscalled superposition. • Entanglement: Pairs of qubits can exist in such a way that two members of a pair of qubits exist in a single quantum state. In such a situation, changing the state of one of the qubits can instantly change the state of the other qubit. This property is called entanglement. Their most promising applications so far include: • Cybersecurity • Cryptography • Drug Designing • Financial Modelling • Weather Forecasting • Artificial Intelligence • Workforce Management Despite their distinct features, both supercomputers and quantum computers are immensely capable of providing users with strong computing facilities. The question is, how do we know which type of system would be the best for high performance computing? A Comparison High performance computing requires robust machines that can deal with large amounts of data - This involves the collection, storage, manipulation, computation, and exchange of data in order to derive insights that are beneficial to the user. Supercomputers have successfully been used so far for such operations. When the concept of a quantum computer first came about, it caused quite a revolution within the scientific community. People recognised its innumerable and widespread abilities, and began working on ways to convert this theoretical innovation into a realistic breakthrough. What makes a quantum computer so different from a supercomputer? Let’s have a look at Table 1.1 below. From the table, we can draw the following conclusions about supercomputers and quantum computers - 1. Supercomputers have been around for a longer duration of time, and are therefore more advanced. Quantum computers are relatively new and still require a great depth of research to sufficiently comprehend their working and develop a sustainable system. 2. Supercomputers are easier to provide inputs to, while quantum computers need a different input mechanism. 3. Supercomputers are fast, but quantum computers are much faster. 4. Supercomputers and quantum computers have some similar applications. 5. Quantum computers can be perceived as extremely powerful and highly advanced supercomputers. Thus, we find that while supercomputers surpass quantum computers in terms of development and span of existence, quantum computers are comparatively much better in terms of capability and performance. The Verdict We have seen what supercomputers and quantum computers are, and how they can be applied in real-world scenarios, particularly in the field of high performance computing. We have also gone through their differences and made significant observations in this regard. We find that although supercomputers have been working great so far, and they continue to provide substantial provisions to researchers, organisations, and individuals who require intense computational power for the quick processing of enormous amounts of data, quantum computers have the potential to perform much better and provide faster and much more adequate results. Thus, quantum computers can potentially make supercomputers obsolete, especially in the field of high performance computing, if and only if researchers are able to come up with a way to make the development, deployment, and maintenance of these computers scalable, feasible, and optimal for consumers.

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Spotlight

CB4

We strive to build revolutionary yet simple solutions that empower retail teams with prescriptive analytics, powered by AI and Machine learning. Our solutions allow retailers to better understand and serve their customers. By applying patented machine learning algorithms on simple sales data, CB4’s software solution captures lost sales by correcting operational inefficiencies on a SKU at store level.

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