A9: (2/2) #DataOps & the selection of the right strategic orchestration tooling will give you that agility to avoid the big punch & get up quickly if you do get hit. Success is always in the journey. We urge everyone to get on that journey ASAP. #eweekchat
A9: (1/2) As Mike Tyson famously said, “Everyone has a plan until they get punched in the mouth.” In business, this means you must plan to be agile & adapt quickly to your challenges. #eweekchat
Q9. A last Big Thought about data analytics – what else should managers/buyers/providers know about preparing for the future of data analytics? #eWEEKchat
A8: We are big believers in #DataOps as a practice. It is powerful because it aligns the data teams, the business leaders & the #IT operations teams focused on delivering real business modernization & innovation outcomes. #eweekchat
A7: (2/2) All the #ML modeling in the world does you no good until it can serve a business outcome that changes the game for your customers – internal & external. #eweekchat
A7: (1/2) Naturally I’m biased. #ControlM, either on-prem or #SaaS, is how we answer this challenge for our customers. We help them simplify their most complex #data pipelines & application #workflows, getting them built, deployed, & running in production. #eweekchat
A6: (3/3) It’s done today in pockets, but it’s time to scale – taking it from project to full-production in a matter of minutes as standard operations. #eweekchat
A6: (1/3) We believe operationalizing #data at scale & speed will continue to be a challenge. Data needs to be ingested, transformed, rationalized & presented to drive insight & action. #eweekchat
A6: (2/3) Creating an #orchestration framework that automates this for our customers irrespective of their application, data, & infrastructure technologies is our mission. #eweekchat
A5: (1/2) This is the $64K question. #GenerativeAI in particular holds amazing promise to mine the vast #data sets within your company. The challenge will be maintaining focus on business outcomes that drive top line growth and cost savings. #eweekchat
A4: (2/2) Both require building a #techstack that is #agile, capable, resilient, error-correcting, and automated. That’s where the rubber meets the road for ‘democratization’. #eweekchat
A4: (1/2) I see two sides to this that must come together to support the idea of #data democratization. Access to data is one side. Having the right, correct data available, for the right people and applications, at the right time, is the other side. #eweekchat
A3: (1/2) We see companies adopting #DataOps practices getting a very positive return on investment. We’re helping them integrate, automate, and orchestrate very complex #datapipelines into the business applications that deliver the desired results. #eweekchat
A2: (2/2) Successful programs have a focus on clear specific business outcomes and strong sponsorship from senior business and #IT leaders in common. #eweekchat
A2: (1/2) Our customers, major global enterprises, are finding lots of success. We see this in many use cases from #supplychain optimization, to hospital network critical care resource planning, to preventative maintenance on production equipment. #eweekchat
@AndiMann It's easy to get lost in dreaming too big, but many of our customers end up delivering really cool data analytics solutions by maintaining their focus
Q1. First, let's look back: How would you describe the evolution of data analytics in the enterprise over the last few years? Do most companies have an effective strategy? #eWEEKchat
A1: (2/2) A big challenge implementing the strategy has been getting applications that rely on highly complex data pipelines into production at scale to drive business outcomes. Getting to production is the hard part. #eweekchat