Welcome to the tech section of my blog, where I share my thoughts and insights on the latest developments in the world of digital, data, and AI. As someone who is passionate about the transformative power of technology, I believe that staying up to date with the latest trends and innovations is crucial to success in this field.
In this section, you’ll find a wide range of articles and posts on topics such as digital transformation, data privacy, artificial intelligence, and more. I’ll share my perspectives on current events, emerging trends, and the future of technology, with a focus on how these developments will impact businesses, society, and individuals.
Whether you’re a technology professional, business leader, or just someone interested in the world of tech, you’ll find plenty of valuable insights and knowledge in these posts. My goal is to make complex topics accessible and easy to understand so that everyone can benefit from the incredible advances happening in the tech world today.
You can also find a lot of technical product reviews on my Amazon reviews page. These are mostly in German.
So, join me on this journey as we explore the cutting-edge world of digital, data, and AI together, and discover new ways to harness the power of technology for a better tomorrow.
Join us for the global launch of Tableau’s super fast data engine, Hyper! Hyper brings faster data refreshes and query performance to Tableau extracts, plus increased scalability in a platform-wide update.
This is your opportunity to get to know the Hyper dev team, hear from Tableau beta customers about their hands-on Hyper experience, and participate in live Q&A. Best of all, learn more about Hyper’s patent-pending technology as well as some of the other features headed your way in 10.5. (Viz in Tooltip, anyone?)
Tableau is hosting the Hyperfest meetup – come and celebrate with the community and the world on the upcoming release of Hyper. In addition to the Hyper presentation, we will also have food, drinks and Tableau swag, so don’t miss it!
Bitfinex ist nun eine geschlossene Platfform, Anmeldung nur noch mit Einladungscode
Seit einigen Wochen ist die Plattform Bitfinex besonders beliebt, da sich dort Ether in IOTA tauschen lässt. Auch die Konvertierung von Euro ist seit einiger Zeit direkt auf der Handelsplattformen möglich. Jedoch ist, auf Grund des Ansturms, Bitfinex seit gestern eine geschlossene Plattform („members only“). Die Registrierung bei Bitfinex ist nur noch mit einem Einladungscode möglich.
Bitfinex-Einladungscodes bald limitiert verfügbar
Sobald Bitfinex neue Kontingente an Einladungscodes freischaltet, werde ich diese nach dem Prinzip first-come-first-served per Email versenden. Sollten Sie Interesse an einem sogenannten Bitfinex Invitation Code haben, können Sie sich hier eintragen:
[contact-form-7 id=“1870″ title=“Bitfinex“]
Binance als Bitfinex-Alternative für IOTA-Handel
Sie möchten mit dem Handel von IOTA nicht auf Bitfinex warten?
Bitfinex ist nicht die einzige Plattform, die derzeit den Handel mit IOTA ermöglicht. Auch Binance bietet IOTA an, die Website gibt es mittlerweile sogar mit deutscher Oberfläche. Dort steht als Handelspaar momentan BTC-IOTA zur Verfügung.
Sie müssen also zuerst Bitcoin kaufen und an Binance senden, wenn Sie auf Binance IOTA kaufen möchten. Falls Sie noch keine Bitcoins besitzen, können Sie welche bei Coinbase (Kreditkarte oder Überweisung) oder bei bitcoin.de (Marktplatz) kaufen.
IOTA attraktiv für Beimischung im Kryptoportfolio
Viele Anleger sehen IOTA zunehmend als interessante Beimischung zur Diversifizierung in einem Kryptoportfolio, wie jenes, das ich kürzlich vorgestellt habe. Einer Twitter-Umfrage zufolge, wird IOTA neben Ripple als zukunftsträchtige Komponente gewertet:
Bitcoin coin symbolizing cryptocurrency investments and crypto portfolio strategies.
Last Friday, it was my pleasure to give an Executive Talk at the Frankfurt School of Finance & Management. While the focus of my presentation was Digital Transformation, plenty of the questions raised by the audience were about cryptocurrencies and how to build a diversified crypto portfolio.
After receiving follow-up emails from participants seeking guidance, I decided to expand on the topic in this blog post. For additional insights into blockchain and artificial intelligence trends, I recommend reading my related post: Digital Banking: The Opportunities of Blockchain, AI, and Machine Learning.
Why Invest in Cryptocurrencies?
The cryptocurrency market has shown explosive growth, with returns exceeding 1200% since early 2017. Finding this kind of return on investment (ROI) elsewhere is challenging. For example, a $500 investment in January 2017 could have grown to $6000 within a year!
This guide provides a framework for building a long-term cryptocurrency portfolio based on diversification and risk management principles.
Crypto Portfolio Allocation Strategy
I recommend balancing your portfolio with up to five coins in the Top 10 market cap, making up 70-85% of your investment, and complementing it with smaller altcoins in promising projects for the remaining 15-30%. This mirrors Timothy Chong’s analysis of Markowitz-style crypto optimization.
Top Cryptocurrencies for Long-term Investment
Bitcoin (40%)
Bitcoin (BTC) remains the foundation of most crypto portfolios, often referred to as „digital gold.“ It is considered a safer long-term investment due to its market dominance and steady growth.
Price (as of time of writing): $16,708
Gain Over Past Year: 2,170%
Market Cap: $278 B (#1)
Circulating Supply: 16,734,237 BTC
Ethereum (30%)
Ethereum (ETH) is the leading platform for decentralized applications (dApps) and smart contracts, driving significant innovation in decentralized finance (DeFi).
Price (as of time of writing): $470
Gain Over Past Year: 5740%
Market Cap: $45 B (#2)
Circulating Supply: 96,272,074 ETH
Litecoin (10%)
Litecoin (LTC) is often referred to as the „silver“ to Bitcoin’s „gold.“ Its faster block generation time (2.5 minutes) and lower transaction fees make it ideal for payments.
Price (as of time of writing): $170
Gain Over Past Year: 4690%
Market Cap: $10 B (#5)
Circulating Supply: 54,255,483 LTC
Ripple (10%)
Ripple (XRP) focuses on enabling fast and low-cost international money transfers. It has gained traction among financial institutions for cross-border payments.
Price (as of time of writing): $0.25
Gain Over Past Year: 3500%
Market Cap: $9.6 B (#4)
Circulating Supply: 38,739,144,847 XRP
Monero (10%)
Monero (XMR) is a privacy-focused cryptocurrency that uses advanced cryptography to ensure transaction anonymity. It has become a go-to option for users seeking privacy.
Price (as of time of writing): $264
Gain Over Past Year: 3370%
Market Cap: $4 B (#9)
Circulating Supply: 15,449,232 XMR
Outlook
As cryptocurrencies continue to evolve, they are likely to become the backbone of decentralized economies. Technologies like smart contracts and blockchain interoperability will pave the way for a seamless global financial ecosystem. In the next decade, we may see tokenized assets replacing traditional stocks and bonds, making financial services more accessible worldwide.
Additionally, privacy-focused coins like Monero will grow in importance as regulators impose stricter oversight, driving demand for anonymous transactions.
Quantum-resistant blockchains could also emerge as a critical innovation, securing cryptocurrencies against future quantum computing threats. The integration of artificial intelligence in blockchain governance may further revolutionize decision-making processes in decentralized networks.
Q: Where can I buy Bitcoin, Ethereum, and other coins? A: Coinbase and Binance are popular exchanges for buying and selling cryptocurrencies. Sign up on Coinbase now and receive $10 in BTC!
Q: How can I securely store my cryptocurrencies? A: Use hardware wallets like the Ledger Nano S or create paper wallets for offline storage.
Final Thoughts on Building a Crypto Portfolio
Building a diversified cryptocurrency portfolio requires careful planning and research. The examples shared in this guide highlight promising projects and balanced strategies to help manage risks.
I welcome your thoughts and questions in the comments or on Twitter:
The Future of Enterprise Analytics: Hyper can handle both OLTP and OLAP simultaneously. In the future it will address NoSQL and graph workloads.
1. What is Hyper’s key benefit?
Hyper is a Hybrid transactional/analytical processing (HTAP) database system and replaces Tableau Data Extracts (TDE). The change will be mostly transparent for end users, other than everything being faster. Hyper significantly improves extract refresh times, query times and overall performance.
2. What is Hybrid transactional/analytical processing?
Hybrid transaction/analytical processing (HTAP) is an emerging application architecture that „breaks the wall“ between transaction processing and analytics. It enables more informed and „in business real time“ decision making.
The two areas of online transaction processing (OLTP) and online analytical processing (OLAP) present different challenges for database architectures. Currently, customers with high rates of mission-critical transactions have split their data into two separate systems, one database for OLTP and one so-called data warehouse for OLAP. While allowing for decent transaction rates, this separation has many disadvantages including data freshness issues due to the delay caused by only periodically initiating the Extract Transform Load (ETL) data staging and excessive resource consumption due to maintaining two separate information systems.
3. Does Hyper satisfy the ACID properties?
Hyper, initially developed at the Technical University of Munich and acquired by Tableau in 2016, can handle both OLTP and OLAP simultaneously. Hyper possesses the rare quality of being able to handle data updates and insertions at the same time as queries by using hardware-assisted replication mechanisms to maintain consistent snapshots of the transactional data. Hyper is an in-memory database that guarantees the ACID properties (Atomicity, Consistency, Isolation, Durability) of OLTP transactions and executes OLAP query sessions (multiple queries) on the same, arbitrarily current and consistent snapshot.
4. What makes Hyper so fast?
The utilization of the processor-inherent support for virtual memory management (address translation, caching, copy on update) yields both at the same time: unprecedentedly high transaction rates as high as 100,000 per second and very fast OLAP query response times on a single system executing both workloads in parallel. This would support real-time streaming of data in future releases of Tableau. These performance increases come from the nature of the Hyper data structures, but also from smart use of contemporary hardware technology, and particularly nvRam memory. Additional cores provide a linear increment in performance.
5. What does this mean for Tableau?
With Hyper now powering the Tableau platform, your organization will see faster extract creation and better query performance for large data sets. Since Hyper is designed to handle exceptionally large data sets, you can choose to extract your data based on what you need, not data volume limitations. Hyper improves performance for common computationally-intensive queries, like count distinct, calculated fields, and text field manipulations. This performance boost will improve your entire Enterprise Analytics workflow.
Julia in Tableau: R allows Tableau to execute Julia code on the fly, enhancing your data analytics experience.
Michael, a data scientist, who is working for a German railway and logistics company, recently told me during a FATUG Meetup that he loves Tableau’s R integration and Tableau’s Python integration. As he continued, he raised the question of using functions they have written in Julia. Julia, a high-level dynamic programming language for high-performance numerical analysis, is an integral part of the newly developed data strategy in Michael’s organization.
Tableau, however, does not come with native support for Julia. I didn’t want to keep Michael’s team down and was looking for an alternative way to integrate Julia with Tableau.
This solution is working flawlessly in a production environment for several months. In this tutorial, I’m going to walk you through the installation and connecting Tableau with R and Julia. I will also give you an example of calling a Julia statement from Tableau to calculate the sphere volume.
XRJulia provides an interface from R to Julia. RServe is a TCP/IP server that allows Tableau to use facilities of R.
3. Load libraries and start RServe
After packages are successfully installed, we load them and run RServe:
> library(XRJulia) > library(Rserve) > Rserve()
Make sure to repeat this step every time you restart your R session.
4. Connecting Tableau to RServe
Now let’s open the Help menu in Tableau Desktop and choose Settings and Performance >Manage External Service connection to open the External Service Connection dialog box:
Enter a server name using a domain or an IP address and specify a port. Port 6311 is the default port used by Rserve. Take a look at my R tutorial to learn more about Tableau’s R integration.
5. Adding Julia code to a Calculated Field
You can invoke Calculated Field functions called SCRIPT_STR, SCRIPT_REAL, SCRIPT_BOOL, and SCRIPT_INT to embed your Julia code in Tableau, such as this simple snippet that calculates sphere volume:
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You can now use your Julia calculation as an alternate Calculated Field in your Tableau worksheet:
Using Julia calculations within Tableau (click to enlarge)
Feel free to download the Tableau Packaged Workbook (twbx) here.
Further Reading: Mastering Julia
If you want to go beyond this tutorial and explore more about Julia in the context of data science, I recommend the book Mastering Julia. You can find it here.
Further Reading: Visual Analytics with Tableau
Join the data science conversation and follow me on Twitter and LinkedIn for more tips, tricks, and tutorials on Julia in Tableau and other data analytics topics. If you’re looking to master Tableau, don’t forget to preorder your copy of my upcoming book, Visual Analytics with Tableau. (Amazon). It offers an in-depth exploration of data visualization techniques and best practices.
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