transformation


ELT with Amazon Redshift – An Overview

#artificialintelligence

If you've been in Data Engineering, or what we once referred to as Business Intelligence, for more than a few years you've probably spent time building an ETL process. With the advent of (relatively) cheap storage and processing power in data warehouses, the majority of bulk data processing today is designed as ELT instead. Though this post speaks specifically to Amazon Redshift, most of the content is relevant to other similar data warehouse architectures such as Azure SQL Data Warehouse, Snowflake and Google BigQuery. First, ETL stands for "Extract-Transform-Load", while ELT just switches to order to "Extract-Load-Transform". Both are approaches to batch data processing used to feed data to a data warehouse and make it useful to analysts and reporting tools.


World AI Show Bangkok

#artificialintelligence

BOOSTING TRANSFORMATION TOWARDS A DIGITAL THAILAND This initiative is in line with the Government's digital roadmap laid out in 4 phases. Phase 1 includes investing and building a digital foundation. Phase 2 ensures everyone can reap the benefits of digital technology. Phase 3 drives the country towards digital technology and innovation while the final phase will help Thailand become a developed country. This is a one of a kind gathering of 300 pre-qualified CIOs, CEOs, CTOs, Heads of AI, Chief Digital Officers, Heads of Innovation and International AI & ML experts among others who will be a part of powerful keynotes, workshops, government and enterprise use-case presentations, product exhibitions, panel discussions and tech talks.


Big Business in Small Business – how SMBs are transforming the Banking Ecosystem

#artificialintelligence

The PACE – Performance Against Customer Expectations – survey has been measuring SMB customer perspectives on banking providers and the impact of technology since 2017. On considering the latest 2019 findings as a whole, four key takeaways emerge: managing customer churn, building out trust, equipping and enabling people alongside technology, and focusing on the user experience. Over the next 18 months to 2 years, I also anticipate a fifth takeaway – embedding social impact by design, as consumers demand a commitment to financial inclusion from their core banking provider, alongside transparent metrics to measure its progress and open dialogue channels to contribute to its evolution. Indeed, SMBs may be small to medium size businesses in terms of employee numbers, but they are increasingly big, innovative and sophisticated business for the banks which serve them and help them to grow. How can you best consider your customers and evaluate their needs alongside the banking, technology and social trends that matter most?


Artificial Intelligence in Enterprise Workshops

#artificialintelligence

Enterprise firms across the globe are increasingly turning to AI-driven technologies to achieve key business goals. While potential benefits are significant, many firms underestimate the fundamental change necessary to successfully integrate AI into the enterprise. Successful adoption programs need to be developed to fit the particular needs of each organization--from its data strategy, project management, and product development to its engagement with the cloud, customers, and partners. This fall, the Laboratory for Innovation Science (LISH), HBS Digital Initiative, and the Harvard School of Engineering and Applied Sciences (SEAS) will kick off "AI in Enterprise," an invitation-only workshop series for selected executives to learn how to manage expectations and assimilate the knowledge and tools they need to implement a successful transition to AI in the enterprise. The first in the series will focus on AI in finance.


Machine Learning Using Hardware and Software

#artificialintelligence

For developers, advances in hardware and software for machine learning (ML) promise to bring these sophisticated methods to Internet of Things (IoT) edge devices. As this field of research evolves, however, developers can easily find themselves immersed in the deep theory behind these techniques instead of focusing on currently available solutions to help them get an ML-based design to market. To help designers get moving more quickly, this article briefly reviews the objectives and capabilities of ML, the ML development cycle, and the architecture of a basic fully connected neural network and a convolutional neural network (CNN). It then discusses the frameworks, libraries, and drivers that are enabling mainstream ML applications. It concludes by showing how general purpose processors and FPGAs can serve as the hardware platform for implementing machine learning algorithms.


How Will AI Reshape the Future of FinTech?

#artificialintelligence

New advances in technology have pushed many sectors, including finance, to start their digital transformation. Some of the emerging FinTech trends today promise to save time and eliminate headaches from the industry, such as fraudulent activity. The change, driven by breakthroughs in artificial intelligence (AI) and machine learning, will transform the financial services landscape and forever change the future of FinTech. And those who want to remain competitive will need to reinvent their business processes as quickly as possible. Although the adoption of AI tech in finance is accompanied by several challenges, Microsoft's Accelerating Competitive Advantage with AI report reveals that global AI investments in the financial sector will reach a value of $5.6 billion in 2019.


What Is The Future Of Enterprise AI?

#artificialintelligence

Due to the increasing involvement of state players in automation warfare, when AI-driven automation is on its way to becoming a war weapon, what will it mean for an enterprise to stay competitive for survival? Artificial intelligence is redefining the very meaning of being an enterprise. The rapidly advancing artificial intelligence (AI) capability is on its way to revolutionizing every aspect of an enterprise. The ability to access data has leveled the playing field and brought every enterprise a unique possibility of progress. What needs to be seen is in this level playing field, which enterprises will be able to compete and lay a new foundation for fundamental transformation and which ones will decline.


Finance Sets A Foundation Of Intelligent Transformation For Growing Businesses

#artificialintelligence

The pace of technology innovation is undeniably moving faster, growing more intelligent, and becoming inescapable. With each advancement, midsize companies are expanding the scope of their digital transformation efforts – from integrating technology into their business to fundamentally changing their workplace culture, organizational operation, and customer experiences. No organization understands this reality better than finance. The IDC InfoBrief, "The Finance Role in Best-Run Midsize Companies: Improving Decision-Making Using Intelligent Technologies," sponsored by SAP, recently revealed that finance organizations in best-run companies are embracing digital transformation and intelligent technologies such as artificial intelligence, predictive analytics, and machine learning. And in return, most of them are improving timely decision-making, running more-efficient and less error-prone operational processes, and empowering knowledge workers to engage in higher-value business activities.


Hadoop vs. Spark – An Accurate Question? techsocialnetwork

#artificialintelligence

I just googled Hadoop vs. Spark and got nearly 35 million results. That's because Hadoop and Spark are two of the most prominent distributed systems for processing data on the market today. It's a hot subject that organizations are interested in when addressing their big data analytics. Choosing the Right Big Data Software; Which is the best Big Data Framework?; How Do Hadoop and Spark Stack Up?


What Is The Future Of Enterprise AI?

#artificialintelligence

Due to the increasing involvement of state players in automation warfare, when AI-driven automation is on its way to becoming a war weapon, what will it mean for an enterprise to stay competitive for survival? Artificial intelligence is redefining the very meaning of being an enterprise. The rapidly advancing artificial intelligence (AI) capability is on its way to revolutionizing every aspect of an enterprise. The ability to access data has leveled the playing field and brought every enterprise a unique possibility of progress. What needs to be seen is in this level playing field, which enterprises will be able to compete and lay a new foundation for fundamental transformation and which ones will decline.