Artificial intelligence (AI) has been a focus for research for decades, but has only recently become truly viable. The availability and maturity of automated data collection and analysis systems is making it possible for businesses to implement AI across their entire operations to boost efficiency and agility. AI has the potential to transform operations by improving three fundamental business requirements: process automation, decision-making based on data insights, and customer interaction.

Talend has a lot in common with our customers. We collect a whole lot of data. We take pride in how we use that data. And we’re always looking for new ways to drive better business outcomes with our data. That is why Talend recently launched the Digital Touchpoint Model (DTM) initiative to create an exceptional, data-driven, “One Talend” support experience for customers, using our own products and innovative best practices.

Extensive coding was once necessary for software development. But while businesses still hire software developers to build an application, low code solutions have changed the game. Enterprise applications are now developed without writing a single line of code. Today, complex applications are developed within hours with low-code or no-code business intelligence (BI) platforms.

As digital transformation accelerates, and digital commerce increasingly becomes the dominant form of all commerce, regulators and governments around the world are recognizing the increased need for consumer protections and data protection measures.

A lack of understanding regarding the role of data in decision-making is a reoccurring challenge for many organizations. However, with the increase in quantity and complexity of data, you need to do everything possible to help your people use data effectively.

Finance has been at the forefront of enterprise analytics for decades. Over the years, these analytics have evolved from reactive, descriptive analytics related to financial performance, treasury holdings, and inventory management to predictive and prescriptive analytics for risk, credit, and financial business modeling.

Modern businesses have vast amounts of data at their fingertips and are acutely aware of how enterprise data strategies positively impact business outcomes. Despite this, only a handful of organisations interact with all stages of the data life cycle process to truly distill information that distinguishes future-ready businesses from the rest.

Today’s enterprise IT organizations are experiencing a massive upheaval due to pressure from employee forces. It’s a familiar story. Just think of the turmoil caused by the dawning of the bring-your-own-device (BYOD) era, with employees demanding to use their beloved personal mobile phones for work.

Hitachi Vantara’s latest improvements to Pentaho make it significantly easier for organizations to move data workloads from on premises to the cloud and back again. The new Pentaho 9.3 Long-Term Support (LTS), part of Hitachi’s Lumada portfolio, offers a cloud deployment option that we anticipate will be a critical accelerant of data-driven transformation.

The skyrocketing value of data has created a global supply and demand for data, data applications, and data services. This new data economy is powered by technologies that enable data access and sharing, including cloud platforms, exchanges, and marketplaces.