Game-Changing Technologies For Today’s Data Scene

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While change has always been a part of the database credo, the growing emphasis on data-driven decision making in today’s economy has resulted in a dizzying plethora of technologies and methodologies entering the market. The number and scope of game-changing technologies are too numerous to mention, and one thing is certain: Database management will never be the same. We have identified some of the most promising technology initiatives, based on discussions with and input from data experts from across the industry spectrum, gathering their views on the key technologies—well-known or under the radar—that are worth watching.


“Streaming data has changed the way companies ingest information and has had an incredible impact on how businesses manage their big data opportunities,” said Bobby Johnson, CTO and co-founder of Interana, and former director of engineering at Facebook. “Enterprises with the biggest competitive advantage empower both data analysts and business users to go beyond aggregate data with the ability to ask iterative questions at a granular level and in real time to fully understand their customers and their business.”

Emerging or widespread? “Leveraging streaming data innovations is conceptually very established, but the adoption is emerging if you look at usage in Fortune 500 companies,” said Johnson. “While the actual big pipe streaming of this data is becoming increasingly mainstream, the parts that are closer to cutting-edge involve what you do after you collect this data, such as behavioral analytics.”

Potential challenges: To support streaming data, visibility and speed of insights are key, “because you must have that clear visibility in seconds—not days or weeks—to understand the diversity of your customer journey and ever-changing market conditions,” Johnson said. “Without visibility, you may never see the data’s richness and depth. The challenge here is that it can be more complicated, but the payoff is that it’s really rich.”

Future prospects: The future of streaming data is robust. “The need for streaming massive amounts of data from every angle of your business is critical for your business insights and planning,” said Johnson. “In 5 years, every decision maker will have clear, reliable data that one can question in real time. Everything you care about—even something as simple as a light switch—is going to be generating information and it’s going to end up in a pipeline, so it’s critical to have access to interactive, real-time visibility of these things.”


For today’s market-savvy enterprises, automated customer data platforms (CDPs) unlock the value in their customers’ data, said Abhi Yadav, CEO of Zylotech. “Automated CDPs solve a variety of data challenges for marketing and sales operations staff members who can miss upsell/cross-sell opportunities simply because their data is not working to their advantage. Their benefit is in consolidating customer data from a variety of siloed sources into one platform that significantly increases the level of insights available to users. Driven by AI, automated CDPs unify the demographic, behavioral, and transactional data of customer records, creating complete views of customer data.”

Widespread or emerging? While it’s a newer generation tool, “CDPs are increasingly seeing widespread use, according to a recent Forbes Insights survey,” said Yadav.

Potential challenges: “The primary roadblock for the adoption of a CDP remains the chaos or noise within the industry,” said Yadav. “As the CDP category has gained momentum in the past few years, many vendors which touch any form of customer data have now begun positioning themselves as CDPs. This makes it difficult for enterprises to quickly understand the relative strengths and weaknesses of one platform versus the other, which in turn makes it more difficult to choose a partner to form a solution around a business problem.”

Future prospects: “Today, only some automated CDPs are enhanced with AutoML (automated machine learning), allowing business operations teams to have self-learning access to their data,” said Yadav. “As these operations teams need a more complete view of customer data in real time to keep up with customer demands, all CDP users will require AutoML as a feature. This will not only make CDPs easy to use for non-technical users but it will give them a powerful capability to stay competitive.”


With inefficient B2B, application, and data integrations with partners, suppliers, and customers, “ecosystem integration software is one technology area where enterprises can significantly differentiate themselves from their competitors,” said Tushar Patel, CMO of Cleo. “Most companies are not keeping up because they are still approaching B2B and application integrations separately. Ecosystem integration software allows enterprises to orchestrate their end-to-end business workflows by taking an outside-in view—creating opportunities to optimize critical business processes.”

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