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Cloud Data Warehouse Trends You Should Know in 2019

In October 2018, TDWI and Talend asked over 200 architects, IT and Analytics managers, directors and VPs, and a mix of data professionals about their cloud data warehouse strategy in a survey conducted in October 2018. We wanted to get real answers about how companies are moving to the cloud, especially with the recent rise of Cloud Data Warehouse technologies. For instance, we wanted to know if a cloud data warehouse (CDW) is seen as a key driver of digital transformation.

Automated Machine Learning: is it the Holy Grail?

Machine learning is in the ascendancy. Particularly when it comes to pattern recognition, machine learning is the method of choice. Tangible examples of its applications include fraud detection, image recognition, predictive maintenance, and train delay prediction systems. In day-to-day machine learning (ML) and the quest to deploy the knowledge gained, we typically encounter these three main problems (but not the only ones).

Data Warehouse Modernization and the Journey to the Cloud

To say that organizations today are facing a complex data landscape is really an understatement. Data exists in on-premises systems and in the cloud; data is used across applications and accessed across departments. Information is being exchanged in ever-growing volumes with customers and business partners. Websites and social media platforms are constantly adding data to the mix.

Spinning up Cloud-scale Analytics is now Even More Compelling with Talend and Microsoft

Today, we're excited to share two announcements that make adopting Microsoft Azure SQL Data Warehouse (ADW) a no-brainer. First, ADW significantly increased the lead over the competition with the new price-performance benchmarks published by GigaOm, showing exponential price-performance improvements over similar solutions.

How Bayer Pharmaceuticals Found the Right Prescription for Clinical Data Access

Like other pharmaceutical companies, Bayer Pharmaceuticals conducts research to discover new drugs, test and validate their effectiveness and safety, and introduce them to the market. That process requires accumulating, analyzing and storing vast amounts of clinical data coming from patients and healthy volunteers, which is recorded on an electronic case report form (eCRF).

Businesses must integrate Artificial Intelligence (AI) now or fall further behind

Artificial intelligence became one of the hottest tech topics in 2017 and is still attracting attention and investments. Although scientists have been working on the technology and heralding its numerous anticipated benefits for more than four decades, it’s only in the past few years that society’s artificial intelligence dreams have come to fruition.

Mastering Data and Self-Development at Lenovo

In 2012 when I worked at Lenovo, the company set out on a journey to create the Lenovo Unified Customer Intelligence (LUCI) platform. The decisions we made with regard to people and technology involved in that project helped to shape my self-development, relationships with others on the team, and relationship with executives.

Are APIs becoming the keys to customer experience?

In recent years, APIs have encouraged the emergence of new services by facilitating collaboration between applications and databases of one or more companies. Beyond catalyzing innovation, APIs have also revolutionized the customer-company relationship, allowing it to provide an accurate and detailed picture of the consumer at a time when a quality customer experience now counts as much as the price or capabilities of the product.