For many years, analysts, problem solvers, and scores of data workers have had to work through the challenges of traditional big data platforms, where ease of use, speed to actionable insight, and the ability to quickly upskill have not always been easy to achieve. Added to these existing frustrations comes an inflection point for many organizations as they evaluate their analytics migration path brought about the need to decide if they will continue with their current legacy analytics capabilities or will move towards a more democratized approach to analytics. A democratized approach to analytics enables the ability to leverage multiple sources of data, create and share insights and build analytic skills quickly is not the sole domain of those with coding skills or access to specialized tools and systems.
There are countless examples where former users of traditional big data platforms have experienced the benefits of self-service democratized analytics through Alteryx. One user in a healthcare organization reflected on the decision to go with Alteryx with the following comment “I haven’t seen any product that has the workflow engine that Alteryx does . . . It just makes sense. [The workflow engine] allows you to do the soup to nuts from data ingestion and scrubbing, [it] takes away a lot of the manual grunt work of re-coding, and [it] helps you spot outliers faster. It makes the data management [and] scrubbing piece much, much easier, and it shortens the whole process from ingestion to getting insight to the end-user” states a review posted on the CLOZD win/loss analysis platform.
Another commenter on G2 Crowd (a user-driven business software review marketplace) said what they like best about Alteryx is the “Ease of use and the ability to bridge the gap between novice data users, coders, and data scientists. Efficiency and repeatability — fast processing and the ability for others (or yourself in the future) to track a workflow step-by-step for cohesive understanding and QA/QC. The Alteryx Community is extremely active and supportive — I’ve learned so much from other users as well as via the great training materials that Alteryx provides.”
As described above, many business leaders face the challenge of taking their organizations to the next level for growth and the ability to navigate volatile markets. These leaders know that having a pervasive data and analytics culture that drives the business forward is critical to having a competitive edge and will drive industry-leading innovation.
Treating data as an organizational pillar is instrumental to reaching their goals. But developing, implementing, and executing an enterprise analytics strategy that supports this vision is a daunting task, even for the most seasoned data executives.
As these organizational leaders make their decisions, they need to be aware of the pitfalls that come with pursuing a traditional big data, legacy-based system approach towards analytics. In a recent report from Radiant Advisors titled “Avoid Strategic Mistakes in Enterprise Analytics”, there are three key areas that those tasked with making decisions for enterprise analytics must consider.
- Don’t outsource your analytics capability. Rather, focus on building a democratized approach towards analytics, where “data and analytics must become one of the organization’s core internal competencies to have a pervasive data culture. It requires an investment — in developing and upskilling existing resources and hiring new skill sets that provide more profound levels of expertise within the data organization.”
- Failing to recognize the value of analytic platforms. There is no shortage of analytic tools out there, but instead of tools that handle only a portion of the analytic process, does the analytic capability under consideration provide a platform that provides all users, regardless of their level of expertise, with a seamless experience?
- Not managing executive press correctly. For those tasked with making decisions on what direction to take their enterprise analytics strategy, it might be easier to align with a business leader who may have an existing or past relationship with a specific vendor they wish to preserve. Or there may be an existing relationship or agreement that the business leader wishes to leverage. The key takes away here is to avoid lock-in scenarios and not yield to pressure when an external vendor insists on exclusively ingesting and hosting your company’s data while delivering black-box style analytics-as-a-service.At the end of the day, the choice made on how to pursue a sustainable analytics enterprise analytics capability needs to come down to what approach will best support the ability to build an insight-driven organization. In this vein, I will refer to another G2 review where a reviewer stated that with Alteryx “a no code platform means you are up and running in minutes and will be an advanced user in a MUCH shorter time than using outdated coding methods. This means more people in the organization can carry out tasks previously isolated to a few people in IT.”
Read more about why Alteryx is a better choice for organizations that want to experience a unified analytics platform that is easy to use and upskills your existing workforce to enable a democratized approach to data.
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