Analytics Myths and Misconceptions Busted
Learn about 6 common analytic myths, and see how you can leverage your existing infrastructure and workforce while you build your analytics strategy.
Common Data and Analytics Myths:
Myth: “To deploy artificial intelligence, we have to invest a lot in exotic new hardware and dedicated infrastructure.”
Truth: You can actually start on the familiar Intel® technology-based infrastructure you already have and scale from there. There’s no need to make large up-front investments.
Myth: “We don’t need advanced analytics like machine learning for our business.”
Truth: All businesses need analytics, no matter what size they or their industry are. What’s important is understanding the key business issues within your own organization and exploring how advanced analytics can help you solve them.
Myth: “We have a lot of data but analytics doesn’t work.”
Truth: It will – you just need to make sure your data is organized, trusted, secured and manageable. There are methodologies and tools available to help you do this.
Myth: “We will need to hire a bunch of data scientists.”
Truth: You can find or build analytics talent within your organization, and provide employees with applications that can turn them into a workforce of citizen data scientists.
Myth: “Measuring everything is good.”
Truth: Measuring for measuring’s sake won’t get you very far. Start with a defined business problem and use that to set your measurable objectives and key performance indicators.
Myth: “Advanced analytics means we need to hire additional IT staff.”
Truth: You can use your existing IT workforce to scale your analytics capabilities. Use your Intel® technology-based platforms for enhanced scale, cost efficiency and flexibility to support your business’ progression to advanced analytics.