Tech News - Data

The Internet of Drones, Oracle OpenWorld updates including AI-infused Oracle cloud, and more in today’s data science news. FlytBase launches AI Platform for Drone applications FlytBase Inc., that has built the world’s first IoT platform for commercial drones – the “Internet of Drones” (IoD) – has released its AI Platform for Drone applications at the the Drone World Expo. Continuing on its mission to bring intelligence and connectivity to commercial drones, FlytBase is enhancing its cloud and edge compute platforms to further integrate AI and machine learning solutions.With recent advancements in data visualization and AI, drones can become autonomous enough to reach near human level performance. On other occasions, AI helps drone process certain unique perspectives and features of the data that are otherwise difficult to get with human efforts. FlytBase said it is extending its platform further to leverage AI solutions for aerial image data. Oracle OpenWorld in News Oracle enhances its cloud with ‘intelligent and adaptive’ apps With Oracle Adaptive Intelligent Apps, Oracle has integrated AI and machine learning functionalities across its cloud applications. The company announced at its ongoing OpenWorld conference that the new apps will infuse AI solutions directly into Oracle Enterprise Resource Planning Cloud, Oracle Supply Chain Management Cloud, Oracle Human Capital Management Cloud and Oracle Customer Experience Cloud Suite. In addition to reacting on real time, the apps can also ‘adapt’ based on the available data and this may significantly help businesses in decision making. “The new AI capabilities combine first and third-party data with advanced machine learning and sophisticated decision science to deliver the industry’s most powerful AI-based modern business applications,” said Steve Miranda, Oracle’s executive vice president of applications development. Oracle cloud offers NVIDIA Tesla P100 GPU instances, V100 GPUs next Oracle announced it is now offering NVIDIA’s P100 GPU instances in its public cloud, with plans to add the more powerful V100 GPUs in the near future. Oracle bare metal cloud is now offering NVIDIA Tesla P100 GPUs for technical computing. Oracle is also working with NVIDIA to offer access to the next generation of GPUs, Tesla V100, based on the Volta Architecture in both bare metal and virtual machine compute instances. The company has called it a game changer of sorts for the customers, in ways that can help them rent a supercomputer by the hour. “Enterprises need accelerated computing to run compute-intensive AI, HPC, and advanced analytics workloads,” Ian Buck, general manager and vice president of Accelerated Computing at NVIDIA, commented on the development. “NVIDIA and Oracle’s collaboration will provide Fortune 500 companies that use Oracle Cloud on-demand access to the world’s most advanced GPU computing technology available.” Oracle unveils Oracle Container Native Application Development Platform Oracle has announced the launch of Oracle Container Native Application Development Platform at its ongoing OpenWorld conference. The frictionless, integrated platform offers a comprehensive suite of cloud services for enterprises to build, deploy, and manage container-native microservices and serverless applications. Oracle Container Native Application Development Platform includes three new services: Oracle Container Engine – a managed Kubernetes service to create and manage Kubernetes clusters; Oracle Container Registry Service – a private container registry service for storing and sharing container images across multiple deployments; and Oracle Container Pipelines – a full container lifecycle management CI/CD service. In its release, Oracle noted that developers want to avoid being locked-in by their cloud vendors, and therefore the cloud-neutral Oracle Container Native Application Development Platform offers them "the nirvana of the true hybrid cloud." In other Data Science News Cloud Firestore: Firebase launches second NoSQL database for app development Firebase, Google’s platform for app development, has launched a new flexible and scalable database service called Cloud Firestore. Designed to query, store and sync app data in a simpler and easier way, Cloud Firestore is a fully managed globally distributed NoSQL document database. Alex Dufetel, product manager for Firebase at Google, said that Cloud Firestore is “strongly consistent” despite being replicated at multiple regions, as it does away with complex use cases so that developing apps gets easier irrespective of the scale. “Delivering a great server-side experience for backend developers is a top priority,” Dufetel said, “We're launching SDKs for Java, Go, Python, and Node.js today, with more languages coming in the future.” Cloud Firestore is now available in public as beta version. John Snow Labs Open Sources the NLP Library for Apache Spark Global data operations company John Snow Labs has released its Natural Language Processing software library for Apache Spark as open source. Written in Scala, the NLP software library contains Scala and Python APIs libraries. “With JSL-NLP, we’re delivering on the promise to enable customers to take advantage of the latest open source technology and academic breakthroughs in data science, all within a high performance, enterprise-grade code base,” said the founding team, adding that “JSL-NLP encompasses a wide range of highly efficient Natural Language Understanding tools for text mining, question answering, chatbots, fact extraction, topic modelling or Search, running at a scale and performance that has not been available to date.” The NLP library will continue to be financially sponsored by John Snow Labs for its development.    

Oracle OpenWorld updates including the first ever autonomous database, Apache Solr 7.0.0 release and more in today’s data science news. Apache Solr™ 7.0.0 available Lucene PMC announced the release of Apache Solr 7.0.0 on September 20. Solr 7 has more flexibility with two new replica types, TLOG & PULL, as updates are handled by replicas based on their types. TLOG can use its transaction log to recover and become a leader, while the PULL type replica cannot become a leader as it does not have a transaction log. In earlier releases, any replica could have become a leader when a leader was lost. Autoscaling is another new feature in Solr 7 that helps manage clusters in simpler ways with more automation. Among other features, the new version also provides rich document parsing, enhanced RESTful APIs and parallel SQL. Oracle OpenWorld in News Oracle 18c: World’s first self-driving database What could possibly be the next generation of industry-leading databases, Oracle has launched the first-of-its-kind fully automated database called Oracle 18c. Calling for automation as essential to preventing and handling data theft, Oracle CTO Larry Ellison announced at Oracle OpenWorld conference the new autonomous database that can patch itself in real time without requiring to go offline. Oracle said their aim is to automate both the threat detection and the immediate remediation, without having a delay waiting for “a human to schedule downtime to gracefully implement a patch in a month or two." Oracle 18c’s data warehouse version will be available in December while the OLTP version will be available in June 2018. Oracle announces AI platform Cloud Service, chatbots to tap deep learning, machine learning capabilities At its ongoing OpenWorld event, Oracle has unveiled the AI Platform Cloud Service that may help developers quickly create and deploy enterprise AI services. The company also announced the availability of intelligent, AI-led chatbots in the Oracle Mobile Cloud delivering multi channel platform to companies for integrating machine learning features. “Oracle AI Platform Cloud instances come pre-installed with familiar AI libraries, tools, and deep learning frameworks, including Caffe, Jupyter Notebook, Keras, NymPy, scikit-learn, and TensorFlow, among others,” Oracle said in its release, adding that machine learning practitioners can access Oracle Object Store and easily connect to existing Spark/Hadoop clusters.The AI-powered bots, that will help automate the information processing and customer conversations, will work with Facebook Messenger, Skype, Slack, Kik, Amazon Echo, Amazon Dot, and Google Home. Oracle Blockchain Cloud Service may enhance security, scalability and supply chains In a major announcement, Oracle has unveiled it enterprise-grade blockchain cloud service. The advanced cloud platform, fully managed by Oracle, is expected to simplify and secure operations with its continuous backup, in-built monitoring, and point-in-time recovery features. “Enterprises can now streamline operations across their ecosystem and expand their market reach with new revenue streams, sharing data and transacting within and outside the Oracle Cloud,” said Amit Zavery, senior vice president, Oracle Cloud Platform. Oracle recently joined the open source consortium for blockchain project Hyperledger. In other Data Science News MathWorks introduces Release 2017b of the MATLAB and Simulink Product Families, adds deep learning capabilities MathWorks has announced its Release 2017b with several new features in MATLAB and Simulink. The release also includes six new products, and, updates and bug fixes to 86 other products. R2017b boosts deep learning capabilities with several features that simplify the way researchers, engineers, and domain experts design, train, and deploy models. “With R2017b, engineering and system integration teams can extend the use of MATLAB for deep learning to better maintain control of the entire design process and achieve higher-quality designs faster. They can use pretrained networks, collaborate on code and models, and deploy to GPUs and embedded devices. Using MATLAB can improve result quality while reducing model development time by automating ground truth labeling,” said David Rich, MATLAB marketing director, MathWorks.

Baidu open sources its Mobile deep learning, IBM’s HPC research and more in today’s data science news. Open source announcements in News Baidu brings AI on smartphones with Mobile Deep Learning Baidu has open sourced Mobile Deep Learning (MDL), a convolution-based neural network customized for mobile devices. MDL can identify objects in an image (taken from smartphone camera) in fractions of second, and give the suggestion to Baidu to carry forward the search process. Coming at faster speed and reduced complexity, MDL supports both iOS and Android, though it may run better on Apple. The codes are available now at Github taking nearly 4 MB space. Last year, Baidu had open sourced PaddlePaddle deep learning package, and developers suggest PaddlePaddle will be best model to use with MDL. With Abseil, Google open sources internal C++ and Python libraries Google has open sourced Abseil, a set of libraries from the very building blocks of its internal codebase. “These libraries are the nuts-and-bolts that underpin almost everything that Google runs,” the company said, adding that Abseil was developed over the last decade to support important projects like gRPC, Protocol Buffers, and TensorFlow. Abseil includes C++ and Python utilities. While the C++ libraries are now available on GitHub under Apache license, Google will soon make available a Python version of the library. In Other Data Science News IBM’s new Deep Learning model can slash computational expense of HPC infrastructure Researchers at IBM’s Dublin research facility claim to have developed a deep learning model that could advance high-performance computing (HPC) by 12,000 percent. Using available conditions of wave, ocean currents and winds, the framework can help in forecasting wave conditions at real time. The research indicates that simulations can be done on lower-end computing devices like Raspberry Pi, and it does not have to require HPC infrastructure. The deep learning model can also be utilized to make the running HPC infrastructure train smartphones or other cheaper computing devices. Royal Bank of Canada tests Blockchain for cross-border fund transfers Canada’s largest bank, the Royal Bank of Canada (RBC), is trialing using blockchain technology for payments to and from the United States. It allows the bank to explore the potential of the tech without fully replacing the existing system. "We wanted to set it up as a shadow ledger so that we can demonstrate our leadership in exploiting that technology while at the same time recognizing that the technology is still early in its adoption phase," RBC's executive vice president Martin Wildberger said, adding that while the technology could prove "transformative and critical," it still needs more time to mature. MapR advances its database to process real-time analytics MapR Technologies has enhanced the scope of its database MapR-DB to drive real-time analytics. The company announced that its latest database version expands the scope for self-service SQL data exploration with enhanced Drill integration, and also supports connectors to native Spark and Hive for real-time processing. The new MapR-DB version also aids real-time application integration with global data capture.

Yahoo open sources Vespa, Salesforce CRM, Dynamics 365 get smarter and more in today's data science news. Vespa: Yahoo open sources internal big data processing and serving engine After Hadoop, Yahoo has just open sourced its most important internal software named Vespa. Yahoo’s parent company Oath, which is owned by Verizon, said in an announcement that it had been using Vespa for content recommendations and searches. Vespa, which is now live on GitHub, dates back to early 2000’s handling around 3 billion ad requests daily. “By releasing Vespa, we are making it easy for anyone to build applications that can compute responses to user requests, over large datasets, at real time and at internet scale – capabilities that up until now, have been within reach of only a few large companies,” Oath said in its release. CRM IN NEWS Salesforce releases Data Studio: A new platform for sharing data on marketing cloud Salesforce has launched a new platform for data sharing within the marketing cloud. The new product, Data Studio, gives the data owners more control in the way they share data and offers marketers better access to relevant data volumes. More importantly, marketers can reach out to their existing customers through artificial intelligence. With Data Studio, publishers have the authority over specific attributes like who are the potential buyers and why are they buying the data, and until what period the data can be used. “Data marketplaces typically provide opaque access to data,” said Raji Bedi, Vice President of Product Management at Salesforce Marketing Cloud, “What our customers desire is the ability to understand the origin, fair rights, and usage of that data. Marketers would prefer to have data with more transparency and a deeper understanding of their audience…this means there's a more targeted reach for marketers and more revenue for data publishers.” Microsoft Adds AI capabilities to Dynamics 365 for Customer Support "Our goal is to increase satisfaction across areas where we engage the customer and within internal support teams who can work more effectively and efficiently," wrote Steve Guggenheimer, corporate vice president of Microsoft's AI unit, in a blog post. "This is accomplished by having virtual agents engage with customers to solve their issues, and seamlessly transfer to support agents only when necessary. The agents receive real-time suggestions when a customer is handed off and can provide real-time feedback to train the virtual agents to become even more effective over time." ML FOR CLOUD IN NEWS First End-to-End Automated Big Data Warehousing Platform launched in Cloud Infoworks said it has released the first and industry’s only end-to-end platform for automated big data warehousing in the cloud which will help organizations “build and deploy big data use-cases in days instead of months.” The platform, Infoworks Cloud Big Data Warehouse, uses advanced automation to handle big data infrastructure reducing the complexity. "We are enabling enterprises to rapidly modernize their data warehouse environments both on premise and in the cloud, and derive strategic value from their big data initiatives," Infoworks CEO Amar Arsikere said, “The unprecedented level of automation built into the Infoworks platform enables enterprises to rapidly design and deploy big data analytics use-cases without any coding." Cloudera Altus Data Engineering: Cloudera partners with Microsoft for Azure cloud platform Cloudera, which has been teaming up with Microsoft in a series of collaborations, has announced the upcoming beta release of Altus Data Engineering for the Microsoft Azure cloud environment. Cloudera Altus Data Engineering on Azure simplifies DevOps and reduces management complexity of infrastructure that are otherwise time consuming. "Enterprise customers increasingly choose Microsoft Azure for their large-scale data processing workloads. We are excited that Cloudera Altus will bring an easy-to-use, end-user focused managed service experience on Azure, that is backed by the proven enterprise-grade Cloudera distribution," said Corey Sanders, who is the director of Compute at Microsoft Azure. "Azure is the only public cloud that provides Azure Data Lake Storage designed for big data at cloud scale. Together with Cloudera Altus, we help customers build, deploy, and share analytics solutions." Hortonworks DataPlane Service will manage and govern data regardless of where it is In what could be a departure from big data architectures that consolidate data into a single data lake, Hortonworks has launched its cloud-based DataPlane Service that will analyze, manage and govern the data across environments, letting enterprises secure their data irrespective of the use case. It will capture data regardless of whether data is in motion or at rest. While DataPlane Service could be a fabric to manage all kinds of data no matter where they reside, its necessity goes beyond infrastructure reasons as data protection laws are getting stringent day by day.

Anaconda brings Python to Microsoft, machine learning in analytics catches fire and more in today’s data science news. Anaconda, Microsoft team up to deliver Python-Powered Machine Learning on MS products including Azure Python data science leader Anaconda has entered into a partnership with Microsoft to deliver “Anaconda for Microsoft”, a distribution that will be available on Windows, MacOS and Linux. With a range of support, Anaconda will be integrated into Azure Machine Learning, Visual Studio and SQL Server. Python codes will now be able to run inside SQL Server cutting down on the requirement to export data, thus improving Python data science performance. Under the partnership, Anaconda users who use R programming language with Anaconda’s R Essentials package can now also avail Microsoft R Open packages. “With Anaconda distributing Microsoft R and Microsoft including Anaconda distribution in Microsoft SQL Server, Microsoft Azure Machine Learning Services and Microsoft Visual Studio, our data platform and cloud customers can do high performance analytics and machine learning with some of the best open source and proprietary frameworks available,” said Joseph Sirosh, Corporate Vice President, Data Group, Microsoft Corp. “By combining both R and Python in SQL Server, we are facilitating the expansion of data science across the enterprise.” ANALYTICS IN NEWS IBM unveils Integrated Analytics System for high-performance data science IBM has introduced a unified data system called the Integrated Analytics System that will support advanced analytics across public, private, or hybrid cloud platforms, including IBM BigSQL and IBM Db2 Warehouse On Cloud Hadoop. Built with IBM common SQL engine and embedded with IBM Data Science Experience and Apache Spark, the new data system simplifies machine learning processing as the data does not have to be moved now for analytics processing where the analytic will take its own time to respond. This gives the users faster and easier access to data science. Splunk boasts of machine learning capabilities across its platform Splunk has expanded its machine learning capabilities further, after deciding to start building in machine learning last year. Key new features include addition of a data cleaning tool, integration of necessary machine learning APIs, and added management support to import user permissions directly into machine learning platforms. Splunk ITSI 3.0 (the new version) can even identify and prioritize issues based on the criticality of the operation. The new advancements are in line with Splunk’s future plan to intelligently automate the task of data monitoring (alerting humans only when it is absolutely required) as customers will soon need tools to cope up with the increasing amount of data and alerts. MemSQL 6: Now developers can run Machine Learning algorithms in SQL environment Popular in-memory database MemSQL has gifted developers machine learning features in its newest version released yesterday. This further brings operational applications closer to data science. “As machine learning use expands within companies, a smarter database is needed to maximize learning,’ MemSQL CEO Nikita Shamgunov said in the announcement, “MemSQL 6 now has capabilities such as extensibility to enable more ML functions, so customers can meet the needs of their most ambitious challenges.”

A new quantum computing language, a self-learning chip called Loihi, and more in today's data science news. Microsoft gifts developers a programming language for quantum computing Considered the next wave of computing revolution, Quantum Computing became one step closer to reality. On day 1 of the ongoing Ignite conference, Microsoft CEO Satya Nadella announced the launch of a programming language toolkit for quantum computing. The programming language will be "deeply integrated into Visual Studio," the tech giant said. The system includes a number of tutorials and libraries to help developers experiment with this new paradigm.The programming language itself has elements of C#, Python, and F# along with new features specific to quantum computing. While developers can use this language on classical computers to try their hand at developing quantum apps, in future, they will be writing programs that actually run on topological quantum computers, Microsoft added. [box type="info" align="alignleft" class="" width=""]Fun Fact: Qubit, the binary bit equivalent for quantum computers, is basically a very small particle that exists in a state of uncertainty (1 and 0) until it exists in a state of certainty (1 or 0).[/box] DEEP LEARNING IN NEWS Intel launches a self-learning chip called Loihi In what could redefine artificial intelligence, Intel Labs has developed a self-learning neuromorphic chip codenamed “Loihi”. It imitates how the human brain operates based on the different types of feedback it receives from its environment. This energy-efficient chip has been developed adopting a first-of-its-kind approach to computing with asynchronous spiking, and it does not require traditional training to learn and make inferences. Just like the brain, Loihi uses the data to understand and then make its inference. What’s more, it also gets smarter over time based on the inferences, Intel said. [box type="info" align="alignleft" class="" width=""]Fun Fact: Loihi (meaning ‘long’ or ‘tall’ in Hawaiian) is an active submarine volcano in the Hawaiian chain.[/box] NVIDIA releases TensorRT 3 AI Inference Software NVIDIA developers can now avail TensorRT 3 release candidate. Claimed to be 40x faster than CPUs at one-tenth of the cost, TensorRT 3 comes with easy to use Python API with improved performance, the company said on its official website. It can deploy TensorFlow models 18 times faster than the TensorFlow framework inference on Tesla V100. DATABASES IN NEWS Microsoft launches SQL Server 2017 that supports Linux On day 1 of the ongoing Ignite conference, tech giant Microsoft announced the general availability of SQL Server 2017 which will run on both windows as well as Linux platforms. This is seems by many as a significant move by Microsoft towards open source. “SQL Server on Linux is an engineering feat,” Microsoft Principal Program Manager Travis Wright said, "The database engine binaries you install on Windows and Linux are literally the same exact files down to the byte. I can attest that even features like Active Directory authentication, backup, and restore all work just the same as on Windows.” The news comes only a year after Microsoft released SQL Server 2016, and the price and licensing model stay exactly the same. SQL Server 2017 will have several enhanced features such as automatic tuning and the much-needed graph databases. There is also an added support for Python programming language which is great news for data science professionals. Oracle makes available MySQL 8.0 first release candidate MySQL, the popular open-source RDBMS, may get a makeover. Oracle, which gained MySQL platform after acquiring Sun Microsystems in 2010, has been stressing on a “mobile-first” approach for modern applications. The new release candidate for MySQL 8.0 which has features like improved JSON support and Unicode 9.0 support among others has been built keeping in mind the requirements for most modern apps. Developers can test the MySQL 8.0 RC1 after downloading the source code from GitHub.

So, you want to learn how to build machine learning algorithms? But where do you start? Becoming a data scientist is a really smart career move – it’s possibly one of the most valuable jobs out there. That’s just one of the reasons it was hailed by the Harvard Business Review as the ‘sexiest job of the twentieth century’ back in 2012. But learning the skills you need to become a truly great data scientist, capable of building powerful machine learning systems with languages like Python and R, isn’t easy. Where do you start? And once you have started, how do you stay up to date with the tools you need to continually deliver valuable data-driven insights? Luckily we’ve got a range of free data science eBooks and free machine learning tutorials to get you started. And once you have got started, we’ve got a wider range of content to help you to continually improve and develop your skills. We think we’ve got everything you need to become a data scientist that can make a real impact in any ambitious and forward thinking organization. Here are our top free data science and machine learning resources that we think you’ll find learning. When learning data science skills and data analysis skills could be so valuable, starting here for free might just be the smartest investment you make today! All you need to do is click the links below, log in, and you’ll find the eBook in your account. You’ll then be able to download the free machine learning guides as PDFs which you can keep forever. Simple.   Learn how to build machine learning systems with Python Python is frequently described as the leading language of data, closely rivalled by R. With this free eBook you’ll learn everything you need to build a range of powerful machine learning algorithms. But it’s not just packed with theory you might learn in a computer science lecture – instead, this free Python eBook focuses on practical examples that demonstrate how to apply machine learning to some interesting problems. From classifying the quality of StackOverflow questions to building an algorithm that can interpret sounds to classify the genre of a given music file, and even topic modelling Wikipedia, you’ll not only be learning the fundamental concepts of machine learning, but also be putting them into practice. Download and read Building Machine Learning Systems with Python for free now. Find out exactly what you need to know about Machine Learning If you’re looking for a shorter, faster introduction to machine learning, you could do worse than this free machine learning eBook. It does exactly what it says on the tin – it gets you up to speed with the core concepts behind machine learning, telling you exactly what you want to know. You’ll find out the three key types of machine learning (supervised, unsupervised and reinforcement learning), the basic tools you need and how to get started on a popular dataset that’s commonly used by anyone that’s just started learning machine learning. With a final Spam detection project, it’s got everything to take you from “where do I start?” to “what next?” Download and read What You Need to Know about Machine Learning for free now. Free Practical Data Analysis Projects We’re passionate believers that there’s no point in theory if you can’t put it into practice. That’s true of all the resources here, but this free data analysis eBook is the perfect way to expand your machine learning skills to become a smart data analyst. Yes, you’ll find more on machine learning, but you’ll also learn data scrubbing, handling multiple data formats, as well as useful data visualization techniques (with the help of D3.js). And when we say practical, we mean practical: Here are some of the practical data analysis projects you’ll find inside this free eBook: Find out how to simulate stock prices with machine learning Predict gold prices with predictive models Modeling infectious diseases with cellular automata Twitter sentiment analysis If you want to get your hands on some interesting datasets, get started with this free data analysis eBook. We think it’s one of the best places to begin your journey into machine learning and data. And if you’re already on that journey, it’s worth checking out – after all, who doesn’t love a personal project (it beats work, anyway). Download and read Practical Data Analysis for free now. With these free machine learning resources and eBooks, you should be well on your way to mastering modern data. So, if you were thinking “where do I start when it comes to machine learning?” you’ll soon be asking “what’s next?!”

Yes, it’s a truism, but we’ll say it anyway: Data Science has changed a lot over the past decade. It has always been central to research institutions – from geographers to chemists, statistics and detailed analysis is a fundamental component of moving knowledge forward. But it’s thanks to technological development that it has radically impacted the business world, and gradually taken over the popular imagination. But what does the data world look like today? It has become so entrenched in modern life, impacting not just business or academic research but also our politics, our shopping habits and even the way we think about love and sex. Nate Silver might have made a name for himself as a data-driven political Nostradamus, but today it’s not even about what we do with data – it’s also about what our robot overlords do with it. Google’s AI appears to have mastered Go better than most of us can begin to dream, and Facebook looks like it might well soon be populated by more chatbots than barely remembered school friends. But what’s driving all this? And who’s building the systems and the infrastructure that has got us to where we are. None of this stuff, after all, builds itself. It feels impossible to predict what’s ahead – so maybe we should stop trying to bother. Instead of thinking the future is out there, locked in our collective imagination, let’s talk more about what we’re doing now – let’s talk more about the trends and pressures that are impacting on real-life data scientists and analysts today. That’s exactly what we want to do here at Packt – whatever you do in data we want to hear from you. Take part in our 2016 Skill Up survey and help us better understand the changing shape of the software world. Tell us what’s important, what tools you’re using – even what you wish you were using. Take part in our survey here and help us not only better understand the software world but also to build a new way to explore it. Once you’ve completed the survey you’ll not only receive a discount code to save 75% on your next eBook or video purchase from Packt, you’ll also gain early access to a beta version of a brand new product we’ve been building – we can’t give much away, but you’ll be able to use it next month, so watch this space! Take the survey now!

What do you need to know to make the most out of your career in data in 2015? We surveyed 20,000 IT professionals to find out what made top data earners their top salaries. Which industry invests the most in its data scientists? Should you learn R or Python to make the most in the field? What are the top tools for data visualization and real insight from your numbers? Skill Up has the answers - discover the state of modern data science by watching our Skill Up results animation, and find out what you need to know to upgrade your career. View the full report here: https://www.packtpub.com/skillup/data-salary-report