This content was produced by Insights, the custom content arm of MIT Technology Review. It was not written by MIT Technology Review's editorial staff. Modern integration platforms are helping enterprises streamline fragmented IT environments and prepare their data pipelines for AI-driven transformation. Enterprise IT ecosystems are often akin to sprawling metropolises--multi-layered environments where aging infrastructure intersects with sleek new technologies against a backdrop of constantly ballooning traffic. Similarly to how driving through a centuries-old city that's been retrofitted for automobiles and skyscrapers can cause gridlock, enterprise IT systems frequently experience data bottlenecks.

Marchex, an artificial intelligence-powered conversation intelligence company, has integrated with platforms from leading communication platform-as-a-service (CPaaS), unified communication-as-a-service (UCaaS), and contact center-as-a-service (CCaaS) providers. These integrations are available via Marchex Anywhere, a new integrations and applications hub. Using Marchex's AI-powered conversation intelligence services, sales; customer engagement; and marketing teams can do the following: "Marchex Anywhere brings our market-leading conversation intelligence services to a rapidly expanding universe of businesses looking to enhance their existing sales, customer engagement, marketing and communication platforms with the power of actionable insights from customer conversations," said Ryan Polley, Marchex's chief operating officer, in a statement. "This reflects Marchex's continued momentum in expanding our conversation intelligence technology and data in innovative and practical ways to deliver the outcomes that customers want." Marchex Zero Code Integrations provide direct data integrations with sales, customer engagement, and marketing platforms, such as Salesforce Sales Cloud, chat systems, Google Marketing Platform, and Adobe Experience Platform.

Editor's note: This feature originally appeared in the March issue of DS News, out now. There are countless ways artificial intelligence (AI) and machine learning (ML) have the potential to transform default servicing--but here are just a few. But how can you make these benefits a reality, and what should you be thinking about in order to maximize the value of AI and ML to your business? Find a technology partner who can help you to normalize the data (ensuring that the data is available in a consistent and standardized format) and to implement data models that can feed into the AI/ML tools. Advanced property servicing platforms are extending their Application Program Interface(API)/Integration capabilities to map out all the key data points across the life of the asset to create a property's digital twin.

WIRE)--SnapLogic, provider of the #1 intelligent integration platform, today announced SnapLogic Data Science, a new self-service solution to accelerate the development and deployment of machine learning with minimal coding. Through SnapLogic's drag-and-drop interface, data engineers, data scientists, and IT/DevOps teams can use SnapLogic Data Science to manage and control the entire machine learning lifecycle – including data acquisition, data exploration and preparation, model training and validation, and model deployment – all from within the SnapLogic integration platform. SnapLogic Data Science breaks down traditional barriers that can undermine machine learning initiatives by providing a common platform for machine learning visibility and collaboration across teams including data engineering, data science, IT, DevOps, and development. According to our recent research with Vanson Bourne, 68% of IT decision-makers consider artificial intelligence and machine learning as vital to accelerating their transformation projects. At the same time, McKinsey Global Institute predicts that the U.S. alone will be short 250,000 data scientists by 2024.

WIRE)--Nov 14, 2018--SnapLogic, provider of the #1 intelligent integration platform, today announced SnapLogic Data Science, a new self-service solution to accelerate the development and deployment of machine learning with minimal coding. Through SnapLogic's drag-and-drop interface, data engineers, data scientists, and IT/DevOps teams can use SnapLogic Data Science to manage and control the entire machine learning lifecycle – including data acquisition, data exploration and preparation, model training and validation, and model deployment – all from within the SnapLogic integration platform. SnapLogic Data Science breaks down traditional barriers that can undermine machine learning initiatives by providing a common platform for machine learning visibility and collaboration across teams including data engineering, data science, IT, DevOps, and development. According to our recent research with Vanson Bourne, 68% of IT decision-makers consider artificial intelligence and machine learning as vital to accelerating their transformation projects. At the same time, McKinsey Global Institute predicts that the U.S. alone will be short 250,000 data scientists by 2024.

Artificial intelligence, immersive technologies, and integration platform as a service are what CIOs should be looking into in 2019. Ahead of Gartner Symposium/ITxpo 2018, Smarter with Gartner reached out to analysts to find out what technologies should enterprises be exploring (or not exploring) in 2019. My focus area is enterprise artificial intelligence strategies. In this area, CIOs should be experimenting with several technologies. Machine learning (ML) based on deep neural networks (DNNs) has made tremendous progress in the past four years and is enabling a new generation of solutions in most industries.

REDWOOD CITY, Calif., May 22, 2018 (GLOBE NEWSWIRE) -- Talend (NASDAQ: TLND), a leader in cloud data integration solutions, has been named to the 2018 CRN Big Data 100 list, a brand of The Channel Company. This annual list recognizes vendors that have demonstrated an ability to innovate in bringing to market products and services that help businesses work with one of the most dynamic, fastest growing segments of the IT industry - Big Data. As a result of Talend's inclusion in the CRN Big Data 100, Solutions Review selected Talend Open Studio for Data Integration and Talend Cloud among its list of "7 Data Integration Tools We Recommend". The data explosion in recent years has fueled a vibrant big data technology industry. Businesses need innovative products and services to capture, integrate, manage and analyze the massive volumes of data they are grappling with every day.

Artificial Intelligence (AI) is getting way ahead of itself. Venture capital is being thrown at anything that claims to have it. Startups are using it as a buzzword that they have to cram into their business idea just to sound like they are on the cutting edge of technology. They say AI is going to take over the world and that it will change the world at a pace faster than anything we've ever seen. Recently, I saw an article about an online retailer that claimed to use AI to make people purchase more often because they could intelligently recommend products to the user.

In this special guest feature, Vince Padua, VP of Platform Innovation, Technology and Design at Axway, discusses the emergence of "digital twin" technology which will revolutionize how industrial enterprises approach manufacturing operations. Digital twins unite physical entities with virtually-modeled "twins" based on technologies like AI and Big Data derived from IoT sensors, ultimately improving the design and execution of manufacturing and maintenance life cycles as well as creating new revenue streams and services. Vince is a platform and product executive spanning cloud, mobile, big data, analytics, and artificial intelligence offerings. He is a leader of global product management, design, and GTM teams that consistently delivered outstanding business results. The myriad uses of big data continue to unfold as new methods of generating, parsing and combining it evolve.

Few terms are hotter today than "artificial intelligence" -- but what exactly does it mean in the real world? On one hand, AI conjures up images of The Terminator, HAL 9000, or other sci-fi scenarios. On the other hand is AI as a force of supreme good or intellectual curiosity, something like IBM's Watson or chess-playing supercomputers. The reality, of course, is somewhere in between. Artificial intelligence is already powering the programs behind many commonplace tools and activities. For example, Google includes machine learning within its search algorithm now, allowing the search engine to tweak itself over time.