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The digital advertising world is evolving at a breakneck pace. By utilizing Hadoop to capture and analyze clickstream, transaction, video and social media data, digital advertisers are able to spot trends and patterns, unearth new relationships, and optimize their ad campaigns by adjusting campaign tactics in real time. Hadoop is being used to increase revenues, understand real-time customer sentiment, increase marketing effectiveness, and increase ratings and viewership. As an example, video game development studios are turning to MapR to analyze massive data streams in order to enhance game player engagement and increase player retention, while music streaming services are providing completely personalized recommendations for their customers.

Financial services organizations around the world are experiencing drastic change. Financial sector companies realize that in order to thrive in a market that has changed so dramatically, they need to be able to improve their operational efficiencies, detect fraud quicker and more accurately, model and manage their risk, and reduce customer churn. To accomplish this, financial services firms are turning to big data technologies and Hadoop to reduce risk, analyze fraud patterns, identify rogue traders, more precisely target their marketing campaigns based on customer segmentation, and improve customer satisfaction.

Government agencies collect vast amounts of data every single day. Big data technologies are now playing a key role in public sector fields such as intelligence, defense, cybersecurity and scientific research. MapR provides government agencies with a cost-effective and scalable architecture that drives real-time analysis, situational analysis, and supports information flow across multiple agencies and departments.

Unstructured data forms close to 80% of information in the healthcare industry and is growing exponentially. Getting access to this unstructured data¡ªsuch as output from medical devices, doctor¡¯s notes, lab results, imaging reports, medical correspondence, clinical data, and financial data¡ªis an invaluable resource for improving patient care and increasing efficiency. See how healthcare providers use Hadoop to tackle the massive amounts of unstructured data.

Manufacturers have traditionally been very successful using data to increase efficiency and quality but are finding that lean production and cost cutting are no longer enough to remain competitive. The goal today is to integrate and gain insights from data across their complex global and often fragmented supply chains. Manufacturers generate and store data from many sources across the supply chain, including process control instruments, supply chain management systems, and systems that monitor the performance of products after they¡¯ve been sold. Being able to access hidden data and integrate all of this data across multiple sources provides valuable insights and competitive advantage.

Oil and gas companies can leverage big data technologies such as the MapR Distribution for Hadoop to collect, manage and rapidly analyze seismic, drilling and production data. Oil companies can leverage this data to gain new insights that help increase drilling and production performance while preventing environmental/safety problems. In addition, MapR can help petroleum companies capitalize on big data in order to optimize their business operations, reduce costs, and increase their competitive edge.

The experience of shopping has changed dramatically in recent years as power has shifted to consumers. Shoppers can easily research and compare products from any device, even while walking through a store. They can share their reviews about retailers and products through social media and influence other prospective customers. The MapR Distribution for Apache Hadoop helps retailers store, integrate and analyze a wide variety of online and offline customer data¡ªe-commerce transactions, clickstream data, email, point of sale (POS) systems, social media and call center records¡ªall in one central repository.

With the explosive growth of smart phones, communications service providers (CSPs) are seeing huge expansion in the volume of data travelling across their networks. While CSPs have always collected voice data, today¡¯s data is much more complex and includes photos, video, streaming music, web browsing, location data, social media, text messages, email, and more. Traditional storage and analytics solutions cannot adequately manage this expanding, diverse volume of data. The MapR Distribution for Hadoop provides CSPs with a cost-effective and scalable platform to ingest, store and analyze their customer data in real time.