We would like to introduce you to our Data & Analytics team at SCS.
Meet Paul, Tim H., Elle, Tim L., Brian, Michael, Erin & Sachin! We took some time to ask them to look into their crystal balls and to give us their predictions for the future of data & analytics. Scroll down to read their predictions! From Microsoft updates to football predictions, they share their insight into what the future could hold!
Paul
“Microsoft will continue to build out the feature set in Power BI so it can better compete with products like Tableau. They will especially focus on the visualization capabilities in Power BI. In the meantime, IT departments are going to get very frustrated with power users pulling in data and creating “rogue” models on their own. Not so long ago, IT managers were dealing with this same challenge as users created Access databases, imported and added data data, and created their own queries and reports.
In many companies, data warehousing and business intelligence is currently used for running operational reports and performing historical analysis–answering the question “What happened in the past?” As these warehouses mature and grow, data science, machine learning, and predictive modeling will be implemented to help answer the question “What does the future look like?” These models won’t be able to necessarily predict the future but they will be able to calculate the probability of specific outcomes–truly business intelligence!”
Tim H.
“My BI crystal ball is telling me that…
- The line between big data and relational data will be increasingly blurred
- ETL process will be able to be configured using natural syntax and basic English
- Data will continue to be more proactive than reactive and users will begin looking ahead more than behind
- More enterprise will incorporate an Enterprise Service Bus using standard micro API’s to move data between systems.
- Developers will increase the amount of consumption of commercially curated data sets
- The Green Bay Packers will continue to be the NFL’s worst team”
Elle
“The demand for self-service, real-time business intelligence that leverages machine learning and predictive analytics will only increase over time. As companies face the pressure to transform from being “[Industry] companies that use technology” to being “Technology companies that specialize in [industry]”, business leaders will need sophisticated, fast and user-friendly data analysis and reporting.”
Tim L.
“There was a time when “Data Warehouse” was the new buzzword. Now, two decades later, it is still a widely used strategy for collecting and organizing data in a way that makes reporting and analysis more efficient (depending, of course, on how efficient the data warehouse design is).
I doubt data warehousing will go away, not in my lifetime, anyway. But I predict a growing trend toward integrating transactional and reporting systems, even for multi-terabyte environments—the same database doing double-duty. Think of the on-going improvements in hardware, lower and lower prices on RAM and SSDs. Combine that with a clever, creative, and experienced data architect, and it’s not hard to imagine reporting and analytics in real time. Without a separate data warehouse.”
Brian
“My crystal ball gazing: We will continue to see the development of easy-to-use tools that allow business users to create their own data visualizations and analysis. These tools will include machine learning algorithms to intelligently assist business users in the creation of analytics.
We will move from data warehouses that actually house a copy of all the organization’s data to data models that seamlessly combine real-time replicas of transactional data into more of a virtual wholistic view of the organization. This will remove much of the latency and complexity necessitated by today’s data warehouses.”
Michael
“Michael predicts that Data & Analytics will be in relaxation mode for the next week until he returns from vacation! ☀️”
Erin
“I see predictive analytics becoming more prevalent in small to medium-sized businesses. With the advancements in machine learning, even businesses with modest amounts of data will begin to leverage the power to try to predict specific measures in the future (increased sales, reduced warranty expenses, etc).”
Sachin
“If I could look into a BI crystal ball, I’d probably see AI take over in dvelopment and application of BI products.”
