Big Data

Data and AI Experts Share Predictions with Databricks: What the Future Holds for AI, Big Data and Analytics

2018 was an unmatched year for the tech industry, with several sectors including artificial intelligence (AI), big data and analytics garnering increased investment and innovation. With 90 percent of enterprises already investing in AI technologies, the steady momentum shows immense opportunities for growth - for both technology providers as well as the customers they serve. Databricks, the leader in unified analytics and founded by the original creators of Apache SparkTM, sees 2019 as the year that more companies solve the world's toughest data problems that have hindered AI initiatives across industries. This perspective is shared by data thought leaders who advise on AI, big data and analytics trends that inspired them in 2018, and those on the horizon for 2019:

Morpheus Data Multi-Cloud Management Platform Powers Self-Service Access to Big Data for EU Member States and Researchers

Today, Morpheus Data announced it has been chosen as the multi-cloud management platform for a strategic EU-wide project which also included technologies from Morpheus alliance partners such as VMware, Dell Technologies, and T-Systems.

This announcement comes at the end of a fiscal year that saw Morpheus Data grow revenue over 3x and increase sales coverage by 6x in response to increased customer, channel partner, and service-provider demand for DevOps-ready multi-cloud management.

According to 451 Research, over 68% of organizations have a hybrid or multi-cloud approach to service delivery. Unfortunately, while agility is the ultimate outcome desired by hybrid IT, increasing cloud and operational complexity has resulted in major organizational friction. Application developers and data scientists are constantly waiting weeks for operations teams to provision services.
 

BlueData Announces General Availability on Google Cloud Platform and Microsoft Azure

Grazed from BlueData

BlueData, provider of the leading container-based software platform for AI and Big Data workloads, today announced the general availability (GA) of its BlueData EPIC software on Google Cloud Platform and Microsoft Azure. This makes BlueData the only unified solution for Big-Data-as-a-Service and AI-as-a-Service with the flexibility to support all three major public cloud services as well as on-premises and hybrid cloud deployments.

Public cloud services continue to be an increasingly popular option for many workloads in the enterprise - including applications for distributed analytics, data science, machine learning, and deep learning. But most enterprises today want the ability to deploy these applications quickly and easily regardless of the infrastructure, either on- or off-premises. They want self-service, elastic, automated, and secure environments for machine learning and analytics - whether the underlying compute and data storage is hosted in one public cloud or another, in their own data centers, or in a hybrid architecture.

Leveraging the inherent infrastructure portability of Docker containers, BlueData is committed to supporting these multi-cloud and hybrid cloud options for Big Data and AI deployments. Last fall, BlueData introduced the initial directed availability of BlueData EPIC on Google Cloud Platform (GCP) and Microsoft Azure - adding to its existing GA support for Amazon Web Services (AWS). And over this past year, BlueData has introduced additional new capabilities for AI, machine learning, and deep learning applications in multi-cloud and hybrid models.

 

Hortonworks and Google Cloud Expand Partnership to Accelerate Big Data Analytics in the Cloud

Grazed from Hortonworks and Google Cloud

Hortonworks, Inc. announced enhancements to its existing partnership with Google Cloud. These enhancements further optimize Hortonworks Data Platform (HDP) and Hortonworks DataFlow (HDF) for Google Cloud Platform (GCP) to deliver next-gen big data analytics for hybrid cloud deployments. This partnership will enable customers to achieve faster business insights by leveraging ongoing innovations from the open source community via HDP and HDF on GCP.

HDP now integrates with Google Cloud Storage, which offers consistent cloud storage for running big data workloads. With HDP on GCP, customers get:

Opportunities for Big Data with Cloud Computing



Article Written by Agnieszka Podemska

The term "big data" refers to sets of structured and unstructured digital data that are too complex and voluminous to be processed by traditional technologies. These sets of data can be mined for information by businesses. Big data is often described using 5 V's: Volume, Velocity, Variety, Veracity and Value. Volume refers of course to the large amount of data that needs to be processed. This data involves e-mail messages, photos, videos, voice recordings and social media posts. Velocity concerns the speed at which new data is generated. Variety refers to different types of data. Veracity relates to the reliability and relevance of the given data. Value equals to the profit businesses can gain by having access to big data. 

In order to store all the data we need innovative big data technologies that go beyond  traditional database solutions. Cloud computing enables efficient big data processing and it is available for businesses of all sizes. The current technological advancements in cloud computing for big data processing open new opportunities for businesses:

Effective Management Solutions for Big Data



Storing, processing, and efficient management are three basic challenges related to Big Data. Presently, there is not a large enough capacity to store the amount of data that has been created in the digital world during the last few years. Big data is the result of measuring and monitoring practically everything going on in the world, creating data at a faster rate than can be stored, processed, or managed by currently-available technologies. Interestingly, the vast majority of Big Data is either duplicated or synthesised data. This surge of unstructured data makes up as much as 80% of new data that must be managed. This has put many enterprises in a position where they need to come up with efficient management solutions for Big Data.

Why Manage Big Data?

The broad concept known as Big Data management encompasses all the technology and procedures used to collect, store, organise, and deliver vast caches of data. It involves data migration, cleansing, integration, and preparation to be used in reporting and analytics. Big Data management is essential because it can improve the accuracy and reliability of analytics. This means your organisation can benefit from quality business insights resulting from the analytics.

Meituan.com Selects Mellanox Interconnect Solutions to Accelerate its Artificial Intelligence, Big Data and Cloud Data Centers

Grazed from Mellanox Technologies

Mellanox Technologies, Ltd. (NASDAQ: MLNX), a leading supplier of high-performance, end-to-end smart interconnect solutions for data center servers and storage systems, today announced that Meituan.com has selected Mellanox Spectrum™ Ethernet switches, ConnectX® adapters and LinkX™ cables to accelerate its multi-thousand servers for their artificial intelligence, big data analytics and cloud data centers. Meituan.com is the world’s leading online and on-demand delivery platform, supporting 280 million mobile users and 5 million merchants across 2,180 cities in China, and processing up to 21 million orders a day during peak times. Utilizing Mellanox 25 Gigabit and 100 Gigabit smart interconnect solutions and RDMA technology, Meituan.com can better analyze and match user needs to merchant online offers, faster and more accurately, while lowering data center operational costs.
 

Talend Releases New Advanced Cloud and Big Data Training for Developers

Grazed from Talend

Talend, a global leader in cloud and big data integration solutions, today announced new courses designed to help advance developers' skills with cutting-edge cloud and big data technologies. Available immediately, the new courses are based on practical exercises that maximize employees' expertise with tools for data mapping and data preparation in the cloud. The new courses demonstrate Talend's commitment to cultivating a skilled workforce that will thrive in the new information age and help further companies' digital transformation initiatives.

"Keeping pace with modern technologies is challenging for companies of all sizes. While innovation fuels powerful business opportunities, it also creates skills gaps in areas such as cloud and big data--where the demand for skilled workers is especially high," said Carrie Anderson, VP of Enablement at Talend. "Data-driven companies need to develop their workforce to keep pace with rapidly evolving market needs and emerging technologies. Thus, training courses that give developers hands-on experience with the latest cloud and big data tools help give companies a competitive advantage."

Splunk Announces New Integrations with Amazon Kinesis Firehose and Amazon GuardDuty

Grazed from Splunk

Splunk Inc., today announced new product integrations with Amazon Web Services (AWS) that span IT, Security, Big Data and IoT use cases. Integrations with Amazon Kinesis Firehose, the first partner integration of its kind, and Amazon GuardDuty deliver Splunk's commitment to continuous innovation for customers. Customers are already leveraging the Amazon Kinesis Firehose integration to stream AWS data into Splunk solutions to manage and enhance their IT and security environments.

"The new integrations make it even easier for Splunk users from IT, marketing, sales, operations and beyond to access and turn AWS data into answers in Splunk Enterprise and Splunk Cloud," said Richard Campione, chief product officer, Splunk. "Splunk is committed to providing a holistic set of AWS integrations that scale to meet our customers' requirements across every use case in IT, Security, Big Data and IoT. The ultimate goal is to provide our joint customers with end-to-end visibility across their entire infrastructure to empower them to make timely, data-driven business decisions."

National Football League Selects AWS as Official Cloud and Machine Learning Provider for Next Gen Stats

Grazed from Amazon AWS and NFL

Today, Amazon Web Services, Inc. (AWS), announced that the National Football League (NFL) has selected AWS's machine learning and data analytics services to boost the accuracy, speed, and insights provided by its Next Gen Stats platform, the NFL's player-tracking system. In choosing AWS to power Next Gen Stats, the NFL aims to develop new ways of visualizing the action on the field, uncovering deeper insights into the action on the field, and expanding the fan experience by offering a broader range of advanced statistics. In addition, AWS will become an Official Technology Provider of the NFL.

Through the use of radio-frequency identification (RFID) tags in player equipment and the football, Next Gen Stats captures a variety of real-time location, speed, and acceleration data. The data is analyzed on AWS and used to contextualize movement on the field for fans to see on NFL Media properties, game broadcasts, third-party digital platforms, and in-venue displays. The data is also leveraged by NFL clubs post game as part of their football operations on a weekly basis. The system creates a variety of unique player and team stats for every game such as a receiver's ability to get open and an offensive line's ability to protect the quarterback. By leveraging AWS's broad range of cloud-based machine learning capabilities, the NFL is looking to take its game-day stats to the next level so that fans and NFL Clubs can benefit from deeper insights.