When it comes to staying competitive, speed to insight is a huge factor inside organizations that want to innovate quickly and grow their business. But for many companies, legacy tools, lack of access to data, and employee skills gaps keep them from moving more quickly.
Creating a framework for faster time to value requires an overhaul of people, products, and processes. How you approach this change will depend on your company. But there are a few universal best practices for getting started.
1. Create a culture of analytics
If asked, most employees will say that they use data to make decisions. But how much data are they really using? Many employees are only using a small dataset, which inhibits their ability to get the full story. According to IDG, the modern enterprise has more than 400 data sources with some organizations pulling from over 1,000 data sources a month. Unless all of this data is readily available via self-service, decisions are being made with partial information.
In order for employees to get the data they need, it’s important to establish a culture that supports data and analytics. IDG reports that professionals at enterprises with more than 1,000 employees, more than half of respondents said that lines of business rely on IT or data teams to build and set up BI and analytics dashboards versus handling these tasks themselves. This slows progress for many employees and their data projects.
In their latest best practices report, TDWI explained that an analytics culture is about fostering leadership, communication, and collaboration. In doing so, organizations can overcome resistance to change and build trust in the process of creating insights from data and acting on them. Without a thriving analytics culture, organizations may experience isolated success, at best, which will do little to lift the entire organization’s data-driven intelligence.
2. Choose the right solutions
So how can organizations make sure their data and analytics do not remain siloed? First, ensure that you use technology that is designed to account for different levels of data maturity. In recent years, technology providers have created frictionless, no code/low code options that can be adopted by most professionals. These solutions have sophisticated, robust features that can support different data management initiatives.
Enterprises find success using cloud data warehouses (CDWs) to scale up data management efforts without procuring more hardware and incurring additional costs. The ability to leverage the power of cloud computing allows data professionals to get projects started quickly, which provides fast business ROI as well.
3. Work smarter
Getting data out of silos and into the hands of stakeholders is paramount to getting to insights quicker. But actionable insights remain an obstacle if teams can’t adequately prepare, integrate, and transform that data.
Investing in processes that allow your team to use data accurately for analytics ensures a better ROI. Make sure your team understands the correct and accurate way to move data to a CDW and what operations to perform on that data to get it into an analytics-ready state.
And when you’re ready for data self-service? Learn the best way to get started with this eBook that highlights:
- How to build a data and analytics strategy
- Where to migrate your data
- Choosing the right tools
- Implementing new solutions
- Getting your team up to speed
Download “5 Steps Toward Data Self Service”