When Faster Data Science Moves the World

by Noah Kuttler, Marketing, IBM Data Warehouse Offerings, IBM

The exact wording may vary, but when speaking about the invention of the lever, mathematician Archimedes is credited with declaring, “Give me a place to stand, and a lever long enough, and I will move the world.”

Today, the leaders in your industry are moving the world to their will with data scientists who use analytics as a lever to generate insights.

Your job is to provide those data scientists with the best place to stand. 

Ideally, it’s a spot where your data scientists have the tools they like to use readily available and your organization’s data is provided to them in a “grab-and-go” format. It’s a spot where they spend less time dealing with processes and more time building their analytics.

Of course, that’s easier said than done. You already deal with data across different locations and platforms: structured and unstructured. In the past, these types of solutions have either been difficult to manage and maintain or they’re not fast enough for today’s requests.

That becomes an issue when you meet with your data scientists or business professionals and the type of analytics they need to run are either performance-dependent or require new types of analytics, like machine learning, that you currently can’t support.

Your strategy must constantly evolve to balance protecting your existing investments and keep an eye on how, and when, you move to the cloud based on your schedule (and not your vendor’s). Finding that “right spot” with the right performance to meet your service level agreements is a balancing act, to say the least.

Unifying Data and Data Scientists with a Unified Data Platform

Recognizing those needs, the IBM hybrid data management family took a dramatic first step when we standardized our portfolio on a Common SQL Engine. Workloads became portable with shared tools, skills and technologies such as data virtualization. And that, in turn, has cleared the way for our latest offering.

IBM is now announcing IBM Integrated Analytics System: a “place” that is going to revolutionize how you move the lever of analytics by bringing your data scientists together with your data. It’s a unified data platform, optimized for performance where your data comes together and is available for use by your data scientists, regardless of where that data is or what format it’s in.

Your data scientists can use the built-in IBM Data Science Experience or they can bring their own tools that they’re already using like Jupyter Notebooks. And the analytics they need to develop, test, deploy and train, like machine learning models, will run where the data resides thanks to the embedded Apache Spark processing engine that runs analytics in-place. The complex and time-consuming process of moving data is eliminated and you benefit from higher performance.

Gaining Speed with Faster Data Science

The IBM Integrated Analytics System server, storage, network and software have also all been optimized to reduce the amount of time and resources required to manage and maintain the system. For instance, we tend not to talk too much about tuning or configuration, because we don’t ask our clients to do it. That’s because the system comes to you ready to run at performance levels that meet your service level agreements and deliver the scalability you need to grow with the business.

And, when you do need to move workloads to the cloud, it can be done seamlessly with integrated tools — allowing you to match your business requirements with the workloads.

If you’re ready to move the world with faster data science, reach out to your IBM sales representative and business partner; they’d be happy to speak to you more about the benefits IBM Integrated Analytics System can provide. You can also learn more by reading this paper on the new world order of analytics.

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