AIIA Presents: RPA & Data Live
Realizing true digital transformation through hyperautomation
Hyperautomation is upon us. RPA lessons have been learned. Cognitive automation has been introduced. The key for global corporate enterprise is to benefit from the collective intelligence presented by RPA and cognitive technologies along with human workers. The key tool to fashion that collective intelligence, is data. Knowing that data is a tool puts you a few steps ahead when the conversation comes around to data being the new oil.
Harnessing RPA Data
So not only is data a tool, it’s also potentially of more value to your enterprise than present cash on hand. But data being the new oil isn’t accurate. There is a direct market for the simple substance of oil. There is no market for your messy data.
You are simply nowhere in intelligent automation and you can go nowhere with artificial intelligence if you haven’t harnessed your data.
Dataset Strategy, Ready Set Vision
The AI & Intelligent Automation Network has reams and reams of content on your structured data and your unstructured data. A decent to good intelligent automation roadmap will plot each data set as well as the means with which to address each data set. A good to above average Chief Data Officer will expound upon the importance of enterprise data and share an inspiring data strategy.
But your enterprise must have an Automation Data Vision to win today, outpace the competition tomorrow and deliver for customers in the future.
Join the AI & Intelligent Automation Network Sept. 29-30 right here on AIIA.net
- Lessons Learned From RPA For Hyperautomation
- Actually Achieving A Data-Driven Business
- Orchestrating True Enterprise Business Intelligence
- Data Insights From Predictive, Prescriptive Predictive Analytics
- Data Enrichment For The Soul Of Your Enterprise
- Attaining Checks & Balances Data Governance
- Expediting Drucker-Inspired Data Management
- Diving in on Data Mining
- Capturing Data Virtualization
- Focusing In On Data Visualization
- Optimizing Your Enterprise Data Platform
- Divining Enterprise Information Management
- Strategic & Operational Database Management
- Masterminding Main Data
Chair Opening Remarks
Data-Driven Decision-Making: The Data Needed Now To Compete In 10 Years
- Answering that question starts with reverse engineering based on the vast data lakes at your disposal
- Where and how are you competing now?
- Do you know if you have what you need to compete in the same space in the future
- Realizing disruptors who are already in your space as well as new space for new disruptors
- How do you gain the data needed to compete with current and ensuing disruptors?
- Beginning with the end in mind by reverse engineering your datasets accordingly
What You Need To Do Now To Gain Insights From Predictive Analytics?
- Ensuring that your data stack is able to keep pace with change is paramount
- Determine exactly what kind of data is required for your future digital enterprise
- Realize where your value-based data sets are located
- Understanding most predictive analytics models are still being run outside of enterprise systems
- Attaining the goal of integrating those models into enterprise systems
Virtualization: Integrating External And Internal Datasets For Future Insight
- Know what you have in your internal datasets
- Know what is missing in your internal datasets
- Find what’s missing internally through external datasets
- Blending your newly formed internal datasets to ensure future value to the enterprise
Visualization: Gaining Enterprise Future Focus
- Realizing the first step to benefiting from data visualization is data cleansing and processing
- Battling the fact that your output has bias because your input has bias
- Overcoming the democratization of data putting too much on your plate
- Ensuring true insights or at the very least-the path to insights vs. pretty pictures
Chair Opening Remarks
Orchestrating Enterprise Business Intelligence For A True Automation Data Vision
- Ensuring your governance truly allows for availability and usability
- Applying your advanced analytics to varietal data sets to gain a holistic view
- Mining to extract insightful data patterns for next generation visualization
- Constantly renewing best practice to ensure inputs, outputs and outcomes continue to guide your vision
BPM & RPA: A Winning Combination
- Marrying BPM and RPA for real business improvement
- Reduce human error by automating mundane, repetitive tasks
- Improve cycle time, process performance and ROI
5 Questions On Conceiving Of An Automation-First Data Strategy
- Who can see all of your data?
- Who has a holistic view of your digital enterprise?
- Who knows what data your digital workforce needs?
- Who knows what the most valuable data is to your enterprise?
- Who knows what data sets you don’t have that you need?
- To scale your digital workforce, these cannot be siloed people
- Blending this intellectually property and intellectual acuity to scale your digital workforce
Masterminding Main Data
- Realizing that your main data problem is a culture problem
- Do your people understand the affect of current data on the future health of the enterprise?
- Understanding that data is your potential chief enterprise value
- Has your CEO gotten behind master data management?
- Aligning the business to ensure your data journey remains on track
- Do business leaders keep in line with governance?
- Consistently returning to policies, practices and procedures to remain master of your domain
Augmenting Your AI Data
- Divining your most valuable data based on enterprise and customer needs
- Applying cognitive tools to optimize and augment your most valuable data
- Increasing accuracy as your cognitive automation tools continually learn from your data
- Realizing both large scale and personalized accuracy for your enterprise, workforce and customer