Gartner recommends that "Effective decision making in an organization will therefore require the convergence of trusted analytics, business processes and data that are married together, instantiated in some execution system or application, and coupled with feedback to help improve the model based on achievement of outcomes."1
It's time to stop talking about your data strategy and start achieving measurable results. Of course, this is no small task when faced with disparate systems, processes, and data sources. An analytics framework that enables faster, more effective decision-making separates good companies from great ones.
BI vendors across the spectrum insist their solution will provide you with the tools you need to finally start to see return on your data strategy. Yet only if you rip and replace existing infrastructure, sacrifice core aspects of your current workflows, or embark on yet another multi-year implementation that requires expensive services. The promises of these solutions always seem to fall short of expectations.
Why is this? What are the key aspects of a successful strategy, and how can it be structured to deliver success all the way, not just part of the way? Start by asking three key questions:
Technology executives must find ways to not only streamline existing data processes, but channel Big Data and IoT streams using flexible, open processes, and machine learning technologies to produce meaningful, reproducible insights. The long-term success of the organization depends on their ability to quickly make sense of this new data and make it broadly available.
CDOs must provide users with shared enterprise tools to analyze data without losing vital governance, oversight, and security. Too often, different participants in the analytics workflow develop affinities for products or processes that cater to their specific needs. While valuable in isolation, it ultimately paints a fragmented picture of the organization.
As data volumes increase and pressing questions require ever-quicker answers, CDOs must equip users across the organization with enterprise analytics tools that make it easy to access and understand data. They need a universal analytics environment where anyone can explore traditional and Big Data—no matter their role, location, or device.
That's why CDOs need an Analytics OS. The Analytics OS is an adaptive analytic platform that provides different capabilities and experiences based on user needs and skills, all while managing content as a shared resource. It is designed to support your organization's entire decision workflow, and give everyone the tools to conduct self-service analytics.
The Analytics OS solves the "last mile problem." It closes the gap between your organization's stated analytics strategy and actual analytics implementation. This allows data leaders to create a universal analytics environment that meets today's analytic needs, and prepares the organization for tomorrow's data and technology challenges.
Pyramid 2018 is the Analytics Operating System. It allows data leaders to bring their data strategies into focus. Pyramid 2018 adapts to your needs and works with your existing resources. Now you can maximize the value of your existing infrastructure and finally start to see the return on your Big Data investments.
Pyramid 2018 gives users the flexibility to build and materialize models back into our in-memory engine, Microsoft's Analysis Services, any ANSI SQL-compliant database technology, and various Big Data engines like Apache Presto and Apache Parquet. With this approach, users can build analytics models "in place" rather than extract them to proprietary intermediary engines that are slow and unwieldy.
It allows technology leaders to simplify data and analytics processes. It provides specific toolsets and functionality that are valuable to any participant in the decision lifecycle. This increases value at not only the department level, but across the enterprise. While user adoption increases, IT and analytics leaders maintain vital visibility into data consumption. That way, analytics can finally start to deliver actionable recommendations for all business needs across the enterprise.
Go here to get started with Pyramid 2018 today!
1Gartner, Inc., 2017 Strategic Roadmap for Enterprise Information Management, Andrew White, 28 March 2017
Source: Pyramid Analytics