WHY IT MATTERS: Digital Transformation

Data cleaning is a massive part of data pre-processing and model building for machine learning algorithms so it's something you can never miss.

The automation, and control of the resulting data, raises questions about the role of human farmers.

12 technology trends that will help shape the future of digital business.

Expert data scientists and other professionals working in data science roles require capabilities to source data, build models and operationalize machine learning insights. Significant vendor growth, product development and myriad competing visions reflect a healthy market that is maturing rapidly.

Finding shabby abodes like these and making them respectable is the load-bearing wall of Amherst’s strategy. Amherst depends on humans to find cities, towns, and neighborhoods where fixer-uppers can become profitable, then relies on automation to pick individual homes. Negri, 31, heads the human team. He spends 150 days a year on the road overseeing Main Street ­Renewal’s operations from Atlanta to Denver, searching for “sweet spot” neighborhoods that combine affordable rents with a strong middle-income employment base.

In this report, TDWI uncovers deeper insights that give users new perspectives on business questions. AI will transform BI and the way people make decisions and act. Rather than start with a hypothesis, data analysts will begin with an AI-driven insight. Instead of querying data to prove or disprove their hypothesis, users will query data to expand or validate a machine-generated insight or recommendation—or they might act on the AI-based insight at face value. But to get to that point, AI-infused BI tools will need to gain people's trust by consistently delivering accurate, relevant, and transparent insights within the context of a business user’s existing workflow.
In the future, AI-infused BI tools will go beyond just surfacing insights; they will recommend ways to address or fix issues, run simulations to optimize processes, create new performance targets based on forecasts, and take action automatically. And yes, machines will make some decisions for us—especially operational decisions in real-time environments. We see this today with fraud detection and online trading systems, but it will become more pervasive.

More than 1,300 people mainly working in the tech, finance and healthcare revealed which machine-learning technologies they use at their firms, in a new O'Reilly survey.

Lors de la soirée du Débat des chefs, bien des choses ont été dites sur Internet, par les électeurs qui suivaient le débat, par les analystes, les sympathisants et même, les partis eux-mêmes. Voici une analyse de ces propos produites par les gens de Semeon Analytics pour chacun des chefs présent lors du débat de jeudi…

• 70% of retail decision makers globally are ready to adopt the Internet of Things to improve customer experiences.
• 73% of retailers rate managing big data as important or business-critical to their operations.
• 78% of retailers say it is important or business-critical to integrate e-commerce and in-store experiences, so an omnichannel experience is delivered to every customer.
• 87% of retailers will deploy mobile point-of-sale (MPOS) devices by 2021, enabling them to scan and accept credit or debit payments anywhere in the store.
• 90% of retailers will implement buy online, pickup in store by 2021.

Now a new breed of software applications is reshaping sales force management. Their common characteristic: Using digital data exhaust, which is the data generated from the regular activities of a sales force or their customers, to change the behaviour of frontline sales representatives in ways that dramatically improve sales productivity and effectiveness.

Onfido delivers next-generation background checks, helping the world’s most innovative businesses verify anyone, anywhere.