At the risk of becoming irrelevant, many legacy companies are making greater efforts to harness cloud-based technology. Dataiku is a data-science platform that provides a collaborative environment for data scientists and business analysts to design and launch data reports and predictive machine learning models. Whether companies are “born in the cloud” or have been around well before cloud popularity, they can optimize what Dataiku refers to as a future-proof platform.

“[It’s] maybe not sexy, but having good reporting and analytics is something that both 200-year-old enterprise organizations and data-native organizations, startups, need,” said Will Nowak (pictured), solutions architect at Dataiku.

Nowak spoke with Lisa Martin (@LisaMartinTV), host of theCUBE, SiliconANGLE Media’s mobile livestreaming studio, and guest host Justin Warren (@jpwarren) during the AWS re:Invent conference in Las Vegas. They discussed how Dataiku serves both native and non-native organizations, as well as what it means to have future-proof data solutions. (* Disclosure below.)

A platform for native and non-native organizations alike

Like a great restaurant, Dataiku provides customers various high-quality options in one central, cohesive setting. The enterprise data-science platform provides a collaborative environment for native data scientists and business analysts. Organizations use Dataiku to build and deploy reports, as well as predictive machine-learning models.

Native data organizations that were born or reborn in the cloud, as well as legacy enterprises, can optimize the Dataiku platform, according to Nowak. Both organizations can benefit from simple charts and graphs that don’t require advanced data analytics. However, “[building] predictive machine-learning models and deploying those as rest API endpoints … to provide a data-driven product for your consumers” is a more advanced use-case, which Dataiku also supports, Nowak explained.

Whether an organization has developers that perform advanced models and analytics, companies can still use Dataiku’s platform for important end results, Nowak added. “[Maybe] you don’t have developers who are very fluent in turning out fast applications. We can give you a place to build a predictive model and deploy that predictive model, saving you time to write all that code on the back end,” he said.

Data quality is also an important concern for various organizations, regardless of their status as natively cloud-based or legacy. Dataiku makes visual indications of data simple. Analysts and data scientists can easily discern if data conforms to quality standards that organizations have established. There is also added functionality regarding data quality, including those that can be configured.

“So, does this column have the appropriate schema? Does it have the appropriate cardinality? These are things that an individual might decide to use,” Nowak stated.

Future-proof data solutions

Artificial intelligence has been a very popular and lucrative trend, which some jokingly refer to as “the hype cycle of AI.” But investing in one particular technology can be a costly risk, potentially locking organizations into technology that could become obsolete. As an open-source platform, Dataiku allows for many languages and their iterances to be adapted and applied for various uses. For example, SQL is the go-to language for data transfer, and the platform is designed to make SQL coding simple, Nowak explained. At the same time, businesses can use the platform with the same ease of use to code in Python, a common language for machine-learning model building.

“[By] leveraging open source, we figured we’re making our clients more future proof. As long as they’re [using] Dataiku to leverage the best-in-breed in open source, they’ll always be where they want to be in the technological landscape,” Nowak stated. 

Users can integrate with Dataiku regardless of the organization’s underlying security mechanisms. For example, “If you’re using AWS and you have IM roles to manage your security, Dataiku can port those and apply those to the Dataiku environment,” Nowak noted.

If someone uses on-prem processing, like Hadoop, they can leverage Kerberos to manage data access. Essentially, Dataiku’s aim is to leverage the best technology the organization already has on-hand and has invested in. “We’re not trying to compete with them, but rather we’re enabling organizations to use these technologies efficiently,” Nowak concluded. 

Watch the complete video interview below, and be sure to check out more of SiliconANGLE’s and theCUBE’s coverage of the AWS re:Invent event. (*Disclosure: Dataiku Inc. sponsored this segment of theCUBE. Neither Dataiku nor other sponsors have editorial control over content on theCUBE or SiliconANGLE.)

Photo:SiliconANGLE