Looking Beyond the Hype of Machine Learning – A Recap of the Q4 2019 ElevateData Dinner

Last week, we hosted an ElevateData dinner, the last 2019 gathering in the series that unites Data Leaders to delve into hop topics in the industry. Just in time for driving New Year’s resolutions, we focused on a headline-generating buzzword and a top-of-mind topic for businesses: Machine Learning (ML). Given the continued commotion around this topic, we wanted to foster a reality check on the progress and potential of Machine Learning with a group of data leaders from different industries and companies. The result was a wonderfully insightful and lively conversation. Here’s what we’ve found:

Machine Learning is still at the beginning of its journey

When asking the data leaders how they define Machine Learning, it was clear that there is still variance in how data science vs. ML vs. AI are defined. Yet, it was widely agreed that we’ve just started to scratch the surface of the potential of ML. It’s interesting to note that the group overwhelmingly agreed that not every business problem requires ML and it is not perceived as a magic solution to throw at any problem. In fact, there are so many business problems across industries where the right solutions are data-related but not ML-driven, like reporting/dashboards, forecasting, inference, experimentation, etc.

Current impediments to Machine Learning

The discussion then focused on what’s standing in the way of Machine Learning delivering on  its promise. Here are the four major obstacles that were identified:

  • Lack of organizational readiness: It seems that many companies and industries haven’t yet reached the maturity level in data infrastructure and optimization/efficiency needs warranting investment in ML. Clear frameworks for measuring the impact need to be defined, tested and implemented. There is also the human factor: in many scenarios, there is  friction around adopting ML, as intelligence and automation delivered by ML are perceived by many as a black box creating loss of control, as well as driving job loss. The group agreed that leadership is critical to ML success. We’ve observed that organizations where Data Science directly reports into the CEO (like Stitch Fix) often see their data endeavors propel.
  • Technology deficiencies: Technology needed to make ML ubiquitous is still in the development phase. This is true for both development and deployment technologies and is leading to inefficiencies in ML solutions production cycle. Many companies are making progress in that direction but we are still far from having a full end-to-end ML solution.
  • Continued ML expertise gap: Despite an abundance of training programs, we continue to have a shortage of true ML expertise which is a combination of multiple skill sets including but not limited to programming skills, full understanding of algorithms’ inner workings, expertise in statistical concepts, and business acumen.
  • Next wave of innovation not enabled: Another factor inhibiting growth is skewed perception of where ML is often considered for optimization and increasing efficiency as opposed to something with a promise to deliver true innovation.

Machine Learning in 2020 and Beyond

After discussing the obstacles standing in the way of ML, the data leaders shared their perspective on driving forces which will help scale ML to next level in 2020 and beyond. Here are the five key takeaways:

  • Moving beyond the buzzword: It seems that the ML overhype is stabilizing. With growing awareness around hype vs. reality, just adding “ML” to every pitch and story is no longer creating the perception of the proposed data product being extra valuable. We are getting better at asking questions to validate the how, what and when about ML. This will help build credibility for ML application.
  • Education and messaging to build real belief in ML: To help ML realize its full potential, data leaders will continue to engage in demystifying machine learning so that it is not considered to be a black box. This will require using the communication tools and strategies tailored to specific situations and org structures. By reducing uncertainty associated with ML solutions, we can truly help unlock the full potential of machine learning. Data leaders will continue to work on positioning ML-driven solutions as enablers for people to do better at their jobs to mitigate the fear of job loss.
  • Focusing on broader data skills in hiring: Industry players are starting to think more holistically about data skills, with a growing acceptance that all data skills are valuable. Data leaders will have proactive conversations on this topic, reenforcing the message that analytical and statistical skills combined with business domain knowledge are  critical to building credible ML solutions.
  • Technology advancement: Through continued investment in ML platform development, some players will emerge with affordable and comprehensive technologies. That would likely speed up the adoption of ML but as development takes off, we would need to remember that ML systems have deeper technical debt challenge compared to software engineering. Therefore, it will be critical to set up the right processes and shape perspectives to ensure sustainable development.
  • Data ethics evolution: ML can lead to negative outcomes due to poor quality data, biases in the modeling, and more. A recent example is the Apple Credit Card controversy, with reports that the algorithm was discriminating against women. There are other scenarios where simple lack of judgment or not thinking through the broader impact of ML can lead to negative consequences. The group wondered if the role of a Chief Ethics Officer will emerge to focus on the ethical usage of data, and it expects an ethics discussion around data usage to become more prominent.

Our guests: Thank you to our guests from Unity, Snowflake, Stitch Fix, Uber, KeepTruckin, Shipbob, ZScaler, Streamlit, SAP Aruba, and Ethos for joining us for this dinner.

Thank you to all of the ElevateData members for joining us and passionately exchanging your ideas, ElevateData would not be what it is without all of you! We can’t wait for what 2020 has in store.

Let us know if you’d like to join this amazing group at the next ElevateData dinner!

Your ElevateData Founders,

Alex, Barkha and Oren 

ElevateData: COVIData and Beyond

For the past two years, we’ve brought members of ElevateData together over dinner each quarter to discuss the latest events and trends, to share practical knowledge, and to predict what the future holds for the world of data. Due to the special circumstances of 2020 and thanks to Zoom, we took ElevateData virtual for the first time last week.

This quarter’s ElevateData featured data leaders from companies like Stitchfix, LinkedIn, Zscaler, Fico, Bitly, Frontdoor, SVB, and Poshmark. The discussion was centered around the impact of COVID-19 to the data organization and their priorities in the foreseeable future.

Here are the top takeaways from our conversation:

COVID-19 Impact

Digital Transformation Acceleration

Many of the Global 2000 have been on the digital transformation journey for the past several years. COVID-19 has catalyzed and validated the importance of digital transformation. This was best said by Satya Nadella during Microsoft’s earnings call in April, “We’ve seen two years’ worth of digital transformation in two months. From remote teamwork and learning, to sales and customer service, to critical cloud infrastructure and security—we are working alongside customers every day to help them adapt and stay open for business in a world of remote everything”. 

The ElevateData group noted that one of the drivers of this accelerated digital transformation has been that the unpredictable and rapidly evolving business environment has brought gaps in digital transformation journey to the front and center of critical decision making. 

As a result, C-suite of many organizations have become fully aware of its value and reprioritized resources to accelerate digitization. Cara Dailey, Chief Data Officer at SVB, shared SVB’s story, saying “COVID-19 really hit the go button on digitization and the ability to have data at your fingertips immediately”. Cara and her team at SVB have long known that data is at the heart of SVB and how they, and financial institutions like SVB, interact with their clients. However, COVID-19 has helped to emphasize this existing priority for SVB’s C-suite.

Data Orgs Resizing

During the Financial Crisis of 2008, Data and Data Science organizations were a shadow of what they grew to in 2020 and during this crisis we’re seeing how they are being affected by a downturn. Some data orgs have continued to grow given their alignment with the C-level and the overall support for data-driven decision making. However, there are other data orgs that have been particularly affected by COVID-19 related layoffs. The group discussed a few potential reasons for this.

  • Data and Data Scientists are expensive resources, particularly with the recent hype around data and data science.
  • Many data and data science bets are longer-term bets. These projects can be deprioritized quickly in a crisis when due to uncertainty, immediate revenue, expense control and profit become the central focus.
  • Given that a small (although growing) number of data executives are in C-suite, value of data in helping to navigate tough waters and prepare for when businesses would turn around is sometimes overlooked by management teams.

As data leaders continue to master succulently and proactively conveying the value of their organization to the C-suite, data teams will strengthen their positioning within the company. The key to conveying the data team’s value is this: Make it simple and don’t go too deep into the technical know-how. In addition, ensuring a good balance between near term and long-term value creation projects will also help data leaders strengthen the value perception of their teams. 

Post-Covid Impact

Data will continue to drive decisions

While we had a thoughtful discussion on COVID-19 impact on Data orgs, the group was long-term optimistic about the value of data to all organizations. The only way to efficiently solve problems with high ROI is with data, analytics, and data science. In times of uncertainty and rapid changes, as expected in the Post-COVID world, data will be even more critical and will continue to grow alongside a digital-first mindset resulting from COVID-19. Things that worked previously might not scale with the spike in demand and the shift to distributed work. Data will continue to be a huge opportunity and the lifeline of many SaaS companies. 

Data Orgs will become even more distributed

The group also expects a positive impact on data organizations from this forced experiment of remote work. Given that all organizations have had to learn to work around the constraints of offices and geographies, there will be more openness to recruiting data talent from a global talent pool. We expect that this in turn will drive the field of data forward. However, innovation is still required in remote working technologies to fully activate efficiencies of distributed data teams. While Zoom and Slack mitigate a lot of data teams collaboration challenges in the new world, at minimum, a good remote whiteboarding tool is needed to augment the remote experience of the data teams.  


Thank you to all of the ElevateData members for joining us and passionately exchanging your ideas virtually during this challenging time.

If you are a Data leader, please let us know if you’d like to join this amazing group at the next ElevateData event!

Your ElevateData Founders,

Barkha, Oren, and Alex

The State of Data – A Recap of the Q1 2020 ElevateData Dinner

Last week we kicked off our ElevateData dinner series for 2020 with our traditional first event of the year, The State of Data. Despite concerns of Covid-19 and increasing financial volatility, we were joined in San Francisco by data executives representing companies like KeepTruckin, Metromile, United Healthcare, Lime, Ethos, Salesforce, Torodata, Layer9, DataCoral, and SVB. We reflected on the progress data made in 2019 and got out our crystal balls to form predictions on how 2020 would unfold. 

Review of 2019 Predictions

First we reviewed a set of 2019 predictions that the ElevateData group made a year ago, and then assigned a grade for each prediction. See how we did below!

  1. Our group had a diverse set of perspectives on consumer sentiment of data privacy in 2019. Several people in the group predicted that 1) consumers will continue to fight for more control over their data, visibility into where it is, how to delete it, and more. On the other end of the spectrum, others predicted that 2) consumers will fatigue on data privacy. And somewhere in the middle, 3) consumers will become more comfortable with less privacy, but will become smarter about their data and what privacy means.

Grade: B | The group believes that we are currently in a paradigm that falls somewhere between the second and third predictions. So while we were not totally accurate in our prediction, we covered the spectrum! 

  1. Blockchain and distributed ledger will help to solve data privacy

Grade: D | The group still believes these technologies could potentially help with  data privacy, but this certainly did not happen in 2019. Instead, we saw a host of data privacy tools like Transcend gain popularity in 2019. 

  1. Big Cloud providers will lead a consolidation in the business intelligence and analytics space (Looker, Periscope, etc.)

Grade: A | Not only were Looker (acquired in 2019 by Google) and Periscope (acquired in 2019 by SiSense) both acquired, but Salesforce announced the acquisition  of Tableau for $15.7bn! We’re excited to see how these cloud leaders will integrate the different businesses and how the next wave of BI and analytics innovations will look like.

  1. More and more data orgs will report directly into the CEO

Grade: C | While the group believes that this is an ideal end-state, it has not yet happened at scale. Many data leaders believe their organizations are still early on the data-driven journey, with roles and hierarchies being reshaped on an ongoing basis. More on this later. 

  1. Bonus prediction we had: AWS will acquire Snowflake

Grade: F | Snowflake remains a private, independent company at the time of this writing so this was a miss. In addition, the Company recently announced a $479MM fundraise at a $12.4bn valuation. The group still believes that Snowflake will continue to be an extraordinarily valuable asset for any of the major cloud providers. 

2020 Predictions

We then set about making our predictions for 2020: 

  1. Decisions and data will be centralized. There is more data and it’s becoming more challenging to know what data users in a decentralized data organization have and what they’re doing with it. A centralized function will enable high ROI from investment in data. 
  2. Data scientists will spend less time reporting out of Business Intelligence and Analytics tools. Instead, data will undergo a process of democratization in 2020 with Self-serve data becoming more prevalent. 
  3. While AI, ML and related technologies will continue to be a critical focus, we will move from hype to a more grounded reality and will find conversations broadening to include other critical topics around data catalogue, quality, accessibility and governance etc which are necessary pillars for all data products including AI and ML. Governance, cataloging, visibility, and monitoring will be critical in 2020 and beyond.
  4. While the ultimate org structure will still report to the CEO, the group was split between Data org directly reporting to CEO vs COO. We agreed that in the organizations where COO is fully running business operations, data orgs will fit well with-in COO org as well.
  5. We’ll see a growing number of novel data technologies born out of tech leaders that are known for their data prowess like Uber, Airbnb, Pinterest, and more. 

Bonus prediction: The Houston Rockets will win the NBA Championship. **Nearly a week after our event, the NBA announced that the 2019-2020 season would be suspended indefinitely due to Covid-19. Not a great start for this prediction but time will tell!

We are curious to see how ElevateData’s 2020 predictions unfold, and we are excited to dive deeper into a few of these topics at our subsequent events this year. One of our favorite themes we discussed at this dinner was that data leaders had grown tired of the hype surrounding AI/ML and other “shiny object” technologies. Instead, data leaders are focused on implementing processes and technologies that can deliver immediate ROI. Given the excitement around this topic, we’re going to focus on it at the next dinner and dive into subjects like Data Cataloging, Management, Governance, insights/inference automation and more. If you’re a data executive and interested in joining our lively events, let us know! 

Your ElevateData Founders,

AlexBarkha and Oren 

ElevateData: Q3:2019 – The Next (Big) Data Tech

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We hosted ElevateData’s Q3 2019 Dinner where we posed the question to the group – What is the Next (BIG) Data Technology? Our discussions covered a full spectrum of data technologies from ingestion to real time/batch processing to machine learning to privacy and security. We loved to hear unique perspectives from companies of all shapes and sizes on what each considered to be most valuable data technology innovation in the last few years – clearly shaped by different business goals and challenges. Some valued the scaling of relational databases while others were more focused on Machine Learning democratization technologies, data governance, and real time data streaming. 

Equally exciting were the opinions shared around what’s to come in data technology disruption in the next few years. We had a lively discussion around technologies like. Data Robots, Serverless, Streaming databases, and the verticalization of SaaS and infrastructure. 

For dessert, we ended with a fascinating discussion on how organizations like Earnest, SVB, Medallia and Poshmark have different frameworks for identifying the need for new data technologies, evaluating the age old question of build vs. buy, and then integrating it in their environment. 

Thank you to all of the ElevateData members for joining us and passionately engaging in exchanging ideas. This event would not have been such a success without your involvement. Here is a list of companies that were represented in the room, let us know if you’d like to join this amazing group at the next ElevateData dinner!

Akita Software, Amazon Music, Bank of the West, DataCoral, DataGrail, Doddle.ai, Earnest, Medallia, SVB, Tonic.ai, Transcend, Unravel Data

Many thanks,

Your ElevateData Founders – Barkha Saxena (Poshmark), Oren Yunger (GGV Capital), Alex Choy (SVB)

Attendees at ElevateData Q3 Event: The Next (Big) Data Tech
ElevateData Founders: (From left to right) Alex Choy (SVB), Barkha Saxena (Poshmark), Oren Yunger (GGV Capital)

Welcome to the ElevateData Blog!

Welcome to the ElevateData blog! ElevateData is an initiative started by Alex Choy, Director at Silicon Valley Bank, Barkha Saxena, Chief Data Officer at Poshmark, and Oren Yunger, Investor at GGV Capital. The mission of this initiative is to scale practical knowledge sharing among data leaders in an environment that fosters open and lively discussions in order to elevate role of data to the next level across all organizations.

ElevateData hosts quarterly dinners on important and relevant data topics. We’ll be sharing the key insights and takeaways from these dinners on this blog.

Finally, we’re always looking to add great data leaders to our community. Please feel free to nominate any one that you think would enjoy joining ElevateData!

We look forward to sharing what we’ve learned and hope to see you at our upcoming dinners and events!

The ElevateData Team,

Barkha, Oren, and Alex