We are so excited to be part of the popular practitioner’s field guide to analytics and emerging tech, returning to Normandale Partnership Center for its fifth straight year on May 30. We can’t wait to explore AI, Machine Learning, Deep Learning, NLP, Robotic Process Automation, Graph Technologies, and much more. Plus, we have an opportunity to speak about hybrid cloud and share some awesome data case studies pertaining to The Weather Company. Although the event is sold out, we will be posting updates on the sessions on our blog, so stay tuned for some great information!
Access to big data, and the insights organizations can gain from analyzing the information, has become a major differentiator. Accessing, organizing, and analyzing data is a great way to get a leg up on your competition, but big data solutions can be complicated, and getting set up with the right architecture can be a bit like navigating a mine field.
Considering these four components, determining the right architecture and analytics platform, and properly putting it all together, can help you get your corporate data strategy off the ground and get you on your way to catching the competition.
1 – Data Platform and Placement
To get the most value from your big data strategy, you need to get the platform right. Knowing your on-premise technologies, cloud infrastructures and “as-a-Service” platforms allows you to see the big picture of what’s available to you, as well as identifies where you may need help.
Assessing your business needs first to build an incremental roadmap that allows you to prioritize your return on investment and mitigate risk ensures a holistic approach as you navigate through all of the elements of your data strategy.
2 – Big Data Analytics
It’s the age-old mantra, quality over quantity. The true advantage of a big data analytics solution is not its volume, but the value it delivers your business. It’s more important for you to gain insight from your data than to worry about the amount. That’s why driving business results is the priority when building a big data analytics solution. Defining the business value of your IT project in a way that is clear and measurable to stakeholders, makes objectives crystal clear.
3 – Data Integration
Analyzing your data in a silo has limited value. With access to integrated data, you can unlock insight that would have otherwise been missed. Consider increasing the impact of your data by seamlessly integrating third party data. Enabling access to data and services can help grow your business and securely and efficiently consuming APIs drives innovation.
4 – Data Security and Resilience
With all that your data provides your business, protecting it is crucial. Data security should be first and foremost. You need to have absolute trust in your big data solution and the people who build and maintain it. Enabling data access while providing protection, making sure your data is available and recoverable is essential to protecting your business.
Whether you are seasoned at extracting all the good stuff from your big data, or just starting to dabble in your organizations insights, it’s never too late to look at your corporate data strategy to make sure you’ve got your bases covered. Getting back to basics and looking at platform options, evaluating the insights which are important to your organization (and that you are seeing the whole picture), and backing up all of that data goodness with an appropriate means is sure to bring any organization’s strategy to the next level.
Many companies have a big data solutions in place. Whether as a pilot program or a solution expanding in scope and use, in 2018 it is time to take that big data strategy one step further. As Mary Shacklett from TechRepublic suggests it is time to integrate and manage your big data analytics with your everyday IT solutions and practices. Ms. Shacklett suggests to focus your strategy on:
- IT Architecture
Many companies’ first step into big data is to adopt a separate solution to pilot. This is a great starting point but as data and insights grow so do your storage and architecture needs. Make 2018 the year you evaluate and integrate. First, spend time evaluating the big data you are storing – prioritize and evaluate what needs to be kept and the best place to store. Next decide how the data generated by your big data solution fits in with the rest of your company data and develop a comprehensive storage strategy. Finally, what steps in 2018 can you take to operationalize your big data. How does this go from a pilot project to being a regular part of everyday analytics, decisions and processes?
Do end users still need to go through IT or a data scientist to access big data? 2018 should also be the year to bring big data to the end user. Work on the back end to ready data into usable formats and research and implement the right big data analytics tools so end users can access and query data to make decisions.
Need help? Evolving Solutions can bring our expertise to you and determine how best to expand, manage and integrate your big data solution with your IT architecture and processes. We can also help you find and implement the best analytics tools for your end users. Learn more.