--- title: "Opera Solutions' Blog: The Hottest Spot for Practical AI and Big Data Science | Hadoop" description: Hadoop | Opera Solutions is the largest independent predictive analytics company in the world, providing Practical AI and Big Data Analytics as an ongoing service to blue-chip clients across the globe. --- [![](https://blog.operasolutions.com/hs-fs/hubfs/Opera_Solutions_Logo_Standard_RGB-72.png?width=369&height=202&name=Opera_Solutions_Logo_Standard_RGB-72.png "Opera_Solutions_Logo_Standard_RGB-72.png")](https://www.operasolutions.com/) ![Blog_Header-4](https://blog.operasolutions.com/hs-fs/hubfs/Blog_Header-4.png?width=3377&name=Blog_Header-4.png "Blog_Header-4") [![Blog_Banner_v3](https://blog.operasolutions.com/hs-fs/hubfs/Blog_Banner_v3.png?width=3713&name=Blog_Banner_v3.png "Blog_Banner_v3")](https://blog.operasolutions.com) ## [The Relentless Progress of Big Data and Machine Learning Technology](https://blog.operasolutions.com/the-relentless-progress-of-big-data-and-machine-learning-technology) Posted by [Anatoli Olkhovets](https://blog.operasolutions.com/author/anatoli-olkhovets) on Tue, Oct 04, 2016 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hubfs/Relentless_Progres_Blog_post.jpg)](https://blog.operasolutions.com/the-relentless-progress-of-big-data-and-machine-learning-technology) --- “Didn’t you just go to a similar Big Data conference recently?” my wife asked me. “How much could have changed in a few months?” I was hesitating about attending another conference in a short time span. My wife is right about most things, but in this case, I am glad I didn’t listen and went anyway. I learned about many new advances in both commercial and open source tools and across the whole technology stack: new hardware, in-memory databases, and new-and-improved tools. [Read More](https://blog.operasolutions.com/the-relentless-progress-of-big-data-and-machine-learning-technology) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Data Science](https://blog.operasolutions.com/topic/data-science), [Signal Hub Technologies](https://blog.operasolutions.com/topic/signal-hub-technologies), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Hadoop](https://blog.operasolutions.com/topic/hadoop), [Spark](https://blog.operasolutions.com/topic/spark) ## [5 Obstacles to Achieving Scalable Data Science, and How to Overcome Them](https://blog.operasolutions.com/5-obstacles-to-scalable-data-science-and-how-to-overcome-them) Posted by [Anatoli Olkhovets](https://blog.operasolutions.com/author/anatoli-olkhovets) on Wed, Jun 22, 2016 - [Tweet](https://twitter.com/share) [![](https://blog.operasolutions.com/hubfs/RunnerHurdles.png)](https://blog.operasolutions.com/5-obstacles-to-scalable-data-science-and-how-to-overcome-them) *The struggle is real — and it’s becoming increasingly apparent to companies that have dipped their toes into popular data science tools. As enterprises test the limits of their new tools, old technology, and data scientists’ time, their infrastructure is starting to show its cracks. Read on to see how these issues are revealing themselves — and more importantly — gather some ideas on what to do about it.* Over the past year, I have been averaging 2–3 customer meetings per week, resulting in over 100 customer and partner conversations around Big Data, analytics, and data science for the enterprise. From these conversations, I have found one key recurring theme: ***scale****.* Large enterprises no longer want to build one model quickly or implement just one use case in production. They all struggle with a large backlog of ideas. They need a way to rapidly turn these many ideas into real use cases that deliver tangible business value. However, many companies simply can’t find a pathway to make this happen. Across my numerous conversations, I noticed very similar patterns and identified 5 common obstacles that can prevent companies from achieving scale for data science. [Read More](https://blog.operasolutions.com/5-obstacles-to-scalable-data-science-and-how-to-overcome-them) Topics: [Big Data](https://blog.operasolutions.com/topic/big-data), [Data Science](https://blog.operasolutions.com/topic/data-science), [Signal Hub Technologies](https://blog.operasolutions.com/topic/signal-hub-technologies), [Machine Learning](https://blog.operasolutions.com/topic/machine-learning), [Hadoop](https://blog.operasolutions.com/topic/hadoop), [Analytics](https://blog.operasolutions.com/topic/analytics), [Spark](https://blog.operasolutions.com/topic/spark) [All posts](https://blog.operasolutions.com/all) ### Subscribe to Email Updates ### Recent Posts ### Posts by Topic - [Big Data (75)](https://blog.operasolutions.com/topic/big-data) - [Machine Learning (38)](https://blog.operasolutions.com/topic/machine-learning) - [Data Science (32)](https://blog.operasolutions.com/topic/data-science) - [Signal Hub Technologies (27)](https://blog.operasolutions.com/topic/signal-hub-technologies) - [Analytics (26)](https://blog.operasolutions.com/topic/analytics) - [Marketing (23)](https://blog.operasolutions.com/topic/marketing) - [Press Releases (22)](https://blog.operasolutions.com/topic/press-releases) - [Arnab Gupta (16)](https://blog.operasolutions.com/topic/arnab-gupta) - [Events (10)](https://blog.operasolutions.com/topic/events) - [Healthcare (10)](https://blog.operasolutions.com/topic/healthcare) - [Signals (10)](https://blog.operasolutions.com/topic/signals) - [Partners (8)](https://blog.operasolutions.com/topic/partners) - [Artificial Intelligence (7)](https://blog.operasolutions.com/topic/artificial-intelligence) - [Competitions (7)](https://blog.operasolutions.com/topic/competitions) - [Supply Chain & Operations (7)](https://blog.operasolutions.com/topic/supply-chain-operations) - [Videos (6)](https://blog.operasolutions.com/topic/videos) - [Mobiuss (5)](https://blog.operasolutions.com/topic/mobiuss) - [Security & Defense (4)](https://blog.operasolutions.com/topic/security-defense) - [Data Equity (3)](https://blog.operasolutions.com/topic/data-equity) - [Customer Yield Management (2)](https://blog.operasolutions.com/topic/customer-yield-management) - [Hadoop (2)](https://blog.operasolutions.com/topic/hadoop) - [OperaNotebook (2)](https://blog.operasolutions.com/topic/operanotebook) - [Practical AI (2)](https://blog.operasolutions.com/topic/practical-ai) - [SoftwareUpdates (2)](https://blog.operasolutions.com/topic/softwareupdates) - [Spark (2)](https://blog.operasolutions.com/topic/spark) - [Transformative AI (2)](https://blog.operasolutions.com/topic/transformative-ai) - [CinemaAI (1)](https://blog.operasolutions.com/topic/cinemaai) - [Data Management (1)](https://blog.operasolutions.com/topic/data-management) - [Data Preparation (1)](https://blog.operasolutions.com/topic/data-preparation) - [Data Quality (1)](https://blog.operasolutions.com/topic/data-quality) - [EMR (1)](https://blog.operasolutions.com/topic/emr) - [Integration (1)](https://blog.operasolutions.com/topic/integration) - [MDM (1)](https://blog.operasolutions.com/topic/mdm) - [Optimization (1)](https://blog.operasolutions.com/topic/optimization) - [Payment Integrity (1)](https://blog.operasolutions.com/topic/payment-integrity) - [Personalization (1)](https://blog.operasolutions.com/topic/personalization) - [Revenue Commander (1)](https://blog.operasolutions.com/topic/revenue-commander) - [Revenue Cycle AI (1)](https://blog.operasolutions.com/topic/revenue-cycle-ai) - [SignalExpressionSyntax (1)](https://blog.operasolutions.com/topic/signalexpressionsyntax) - [Telecommunications and Media (1)](https://blog.operasolutions.com/topic/telecommunications-and-media) - [TravelAI (1)](https://blog.operasolutions.com/topic/travelai) - [predictive analytics (1)](https://blog.operasolutions.com/topic/predictive-analytics) - [revenue cycle management (1)](https://blog.operasolutions.com/topic/revenue-cycle-management) see all [![Opera Solutions](https://www.operasolutions.com/themes/opera/logo.svg)](http://operasolutions.com/) © Opera Solutions OpCo, LLC. 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