2850: From Data Overload to Insight: Sigma Computing's Blueprint for Business Intelligence

[00:00:00] Have you ever wondered how the vast oceans of data generated by businesses every single

[00:00:07] day can be harnessed not just to inform decisions but actively drive innovation and efficiency

[00:00:13] across the entire organisation? Well today on Tech Talks Daily we're going

[00:00:19] to be diving into the world of business intelligence and data analytics with a special focus

[00:00:24] on how technology is evolving to meet the ever changing needs of businesses and joining me

[00:00:30] today I've got Mike Palmer he's the CEO of Sigma Computing and I've invited him to join me

[00:00:38] on the podcast today to shed light on how Sigma is leading the change in making data analytics

[00:00:44] not only more accessible but also more integral to business strategy and operations allowing

[00:00:51] technology to be seen as a business enabler so from the evolution of business intelligence

[00:00:57] to the pivotal role of high quality data and the pathway to sustainable tech growth today I want

[00:01:03] to uncover how organisations can leverage data to not just survive but thrive in today's competitive

[00:01:10] landscape. Now before I get today's guest on quick shout out to the sponsors of Tech Talks Daily

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[00:01:52] to secure your data and empower your business but now let's get today's guest on

[00:01:58] so buckle up and hold on tight because today I'm going to beam your ears all the way to San Francisco

[00:02:05] where you can sit down and enjoy a lovely conversation with myself and Mike Palmer CEO of Sigma Computing

[00:02:13] so a massive warm welcome to the show my can you tell everyone listening a little about who you are

[00:02:18] and what you do I am the CEO of Sigma Computing I joined here about four years ago and joining

[00:02:25] co-bodders Rob Willand and Jason France and they were on a journey to build a data product

[00:02:31] that was accessible to everyone that was kind of a core philosophy and I really having built a

[00:02:37] career in tech really felt like this was kind of the next wave and has been excited to be here

[00:02:45] ever since then and things like business intelligence cannot often be very confusing daunting or

[00:02:51] overwhelming for people outside of that space one of the things I try and do every day is demystify

[00:02:57] different areas in technology and business and the impacts that they're both having on one another

[00:03:02] so Sigma Computing is described as not just another business intelligence tool but a revolutionary

[00:03:08] cloud analytic solution with a spreadsheet like interface that scares me because that's not my world

[00:03:13] but can can you explain how this unique interface facilitates data exploration at cloud scale

[00:03:20] and speed and why it's particularly effective for businesses across so many industries because

[00:03:25] you're solving real well problems here right we are you know we are across every vertical we're

[00:03:30] across every department which is really unique in the software world you know we're coming from a

[00:03:34] world where in particular Silicon Valley built products for technical experts and you know we

[00:03:40] really set out to appeal to the everybody and and we'll talk a little bit about that spreadsheet

[00:03:45] interface but we offer an interface for all kinds of different skill sets whether they are Python or

[00:03:52] SQL or natural language or of course you know of course the spreadsheet but I would stand back

[00:03:57] and say you know Sigma is an experts data tool built for all of us you know and I think that

[00:04:02] that core idea that the average person that shows up to an enterprise every single day wants to be

[00:04:08] empowered to do their job the kind of what's changed is that over the last 10 or 15 years as the world

[00:04:14] adopted public cloud where the volumes of data have exploded where the compute capacity to take advantage

[00:04:21] of that data is also exploded all of this has become increasingly cost effective and then we had

[00:04:27] these amazing databases that were deployed on top of the by companies like snowflake and data bricks

[00:04:33] that really changed the infrastructure worked but it didn't change much for the people trying to

[00:04:38] access that data and that's where sigma comes in and while I definitely appreciate your point

[00:04:43] that your world may not be spreadsheets spreadsheets are the way that most people do their jobs today

[00:04:49] they learned that skill starting when Microsoft Excel launched in 1985 and if you look at

[00:04:55] the product today it's more or less the same product this many decades later they're super

[00:04:59] comfortable working in rows and columns and we have found a way to capture the power of all of

[00:05:07] the cloud developments with the simplicity of the spreadsheet interface that people do their jobs

[00:05:13] and every day it put those two things together you create that level of empowerment

[00:05:17] uh and that empowerment because it's a such a universal skill that empowerment is in every vertical

[00:05:23] it isn't every department and it is global yeah 100% with you there as you said it is a universal

[00:05:30] skill that people can just pick up and play straight away and one of the things that that put you on

[00:05:34] my radar I was looking at your recent New York Stock Exchange for all talk interview and in this you

[00:05:40] touched upon various topics including the evolution of business intelligence over the years so

[00:05:46] I'm curious from your perspective how has business intelligence evolved in recent years and

[00:05:52] and what role does sigma play in that transformation because so much has changed in this space hasn't it

[00:05:58] a lot has changed in the space for sure uh you know and I think that the first thing to recognize

[00:06:03] about bi or better said about the industry in general is that we're kind of emerging from the

[00:06:07] era of infrastructure into the data era and I kind of focus on this because it would have been

[00:06:13] really difficult to take advantage of large scale data if you didn't have large scale compute storage

[00:06:20] and database platforms underpinning it and bi lacked that underpinning the i was always constrained by

[00:06:28] the fact that it was attached to some sort of application in some sort of data silo and uh we

[00:06:34] in effect created another layer of complexity on that with bi where some expert that really knew

[00:06:39] how to write sequel or build a dashboard for you had to sit between you and the data you needed to do

[00:06:45] your job and so as a result bi's definition uh was constrained by the infrastructure and it basically

[00:06:51] became can I get a chart for historical data that's been bi since almost day one and users don't really

[00:07:01] want that you know that is a component of what they need to do their jobs so in that floor talk

[00:07:07] you know what I was alluding to here is if you step back and actually ask user what they need

[00:07:12] they definitely need that want a perspective on the past they want to know what the trend looks like

[00:07:16] but no one gets paid uh to tell you history people get paid to forecast the future and make decisions

[00:07:23] and that's what the spreadsheet has been about the spreadsheet is where we put our forecasts

[00:07:28] the spreadsheet is where we add our data input the spreadsheet is where we reconcile things that

[00:07:33] don't make sense and what stigma has done is taken all of the benefits of bi but combine them with

[00:07:40] all of the benefits of spreadsheets so now the definition of the i can be much broader the i can give

[00:07:46] us history but bi can also collect data from the end user create forecasts do that on live data

[00:07:54] do it in real time do it collaboratively so now we could do our jobs by coming in every day and

[00:08:00] having the best view on the data we've had from history provide various views on what the future might

[00:08:06] look like and then ultimately by the way because it is live automate the outcomes as well

[00:08:12] so what sigma is proud of here is not necessarily being next gen bi and it back me sort of recoil

[00:08:18] description we want to change the whole definition of what it means for the average person to leverage

[00:08:24] data to trend history to create forecasts to execute on my data to collaborate across the enterprise

[00:08:31] and ultimately create automations to make them more successful in their jobs

[00:08:36] and something else i wanted to bring up with you today is the explosion of data sources from so

[00:08:41] many different areas now and by that i mean everything full mobile to iot devices and i think

[00:08:47] as everybody's oh so many businesses in so many different industries are facing the challenge of

[00:08:51] turning an increasingly fast amount of data streams into actionable it's sites so with that

[00:08:57] in mind is anything you can share around the importance of elements such as data awareness accuracy

[00:09:04] collaboration and governance in achieving that data driven success because it can feel that

[00:09:09] again quite daunting with so much data there or and we've all seen what happens with garbage in

[00:09:16] and go a bit of a fine ult to this isn't there is definitely always going to be a balance you know

[00:09:23] and we talk in huge scale our customers have hundreds of billions of records and growing at a rapid

[00:09:29] rate and on the positive side due to some of the infrastructure unlocks we have the opportunity

[00:09:36] to now make data a core strategy and a core differentiator we think about financial services companies

[00:09:42] at their core their data arbitrage businesses i think that idea is about to come to all vertical

[00:09:48] industries where people look at the data that they have they want more of it they want it from

[00:09:53] different sources because diversity is a good thing in data uh and they want to then be able to

[00:09:59] have their unique view of the world now the question to the jurorsky men is okay we have huge amounts

[00:10:04] of data coming from everywhere how do we know that it's good data how do we know we're getting it

[00:10:08] into the right hands uh and you're right sigma therefore has to strike the balance between

[00:10:13] abscess for the everybody but at the same time providing tools that make sure that the data is

[00:10:18] well governed that the data is accurate and then it reflects kind of what the enterprise wants

[00:10:22] that person to pursue so we provide tools to do that we provide the ability to create approvals on

[00:10:30] data sense we have metrics capabilities so that for example when an enterprise says this is the revenue

[00:10:36] formula that the whole enterprise use that formula and they don't create a different one uh that

[00:10:42] sort of ideas build in the product and the same time we do something that is far better than the

[00:10:47] average data product and that is when we allow that end user to interact with data the data itself

[00:10:54] never leaves the customers where it's and as a result uh security has maintained lineages maintained

[00:11:01] there's telemetry on every single action that's taken we have a very unique feature where we allow

[00:11:07] and users to add data to the warehouse through sigma and again because the data stays in the warehouse

[00:11:12] we know who added it when they added it and what they added so the idea that we can take a lot of

[00:11:19] empowerment and combine it with a big safety net of security and governance is really at the core

[00:11:25] of what sigma is and as you said there it's the importance of good data and I've been read about sigma

[00:11:32] I know that you aim to make high quality decisions based on high quality data and if we don't look

[00:11:38] under the hood here is that and if you can share around the kind of strategies or indeed technologies

[00:11:42] that you employ to ensure that data used by organizations is both accurate and accessible and

[00:11:48] faster that culture of informed decision making because I think so many businesses around the world

[00:11:53] that they're all pushing forward with data driven decision money king so important but it's

[00:11:58] again getting that balanced right and having the right strategy the right technology in place right

[00:12:04] and that I mean the story of enterprise productivity is the story of technology

[00:12:09] and I'd like to start with accessibility right accessibility for people

[00:12:14] and getting access at this data which is increasingly the most important asset that an

[00:12:18] enterprise has is where the conversation has to start and sigma's the only platform today on the

[00:12:26] market that allows the diversity of access points as I said before whether you're a data scientist

[00:12:32] and you're writing Python or you are a spreadsheet user because you've been working in the inventory

[00:12:37] team or you want to engage with natural language via AI or that you write SQL because you've got your

[00:12:43] history in either the database or yeah you can do all of that in sigma and more importantly

[00:12:48] is that you can choose the access point for the for the job you're doing and know that the work

[00:12:54] that you're doing is shareable across all the other different types of skill sets so this combined

[00:13:00] idea that I can choose one platform as an enterprise roll it out globally know that everybody in my

[00:13:06] company has a skill that can leverage that platform but also know for the first time that I connected

[00:13:12] all of those users and so that they are more than the sum of their parts is an unlock for most

[00:13:19] enterprises now coming back to the idea that if we've enabled all these people how do we make sure

[00:13:25] that what we're giving them is truly the right data that it is the right analysis and this is where

[00:13:32] when you employ everybody at when I refer to often as the periphery right we have people in

[00:13:37] warehouses and retail stores and hospitals we have them all over the world at our enterprise

[00:13:45] but one of the challenges we've had is that in the center we have very little visibility to the

[00:13:51] periphery and sigma solves that problem if you're working in a large bank or you're working at a

[00:13:56] retailer with outlets for the first time my person in the field can add data and view data and mill you

[00:14:04] know say million miles away but then you'd be in space that you could be many thousands of miles

[00:14:09] away and you will be able to see in real time what is this person looking at what data are they

[00:14:16] accessing what input did they provide that now by the way I can make decisions on because I have

[00:14:21] access to so this idea of connecting the periphery to the center because we've enabled the entirety

[00:14:27] of the periphery is the unlock for accurate data acted on in real time so if we would assume

[00:14:34] out just for a moment and try and look at the broader picture here including everything from macro

[00:14:39] economics to future tech predictions I'm curious how do you see the role of things like cloud

[00:14:45] analytics and tools like sigma evolving to meet the needs of diverse VC audiences especially when

[00:14:52] analyzing markets and performing due diligence because it feels like the speed of technological

[00:14:57] changes moving a break next speed but there's also that realization it might never move this slow

[00:15:02] again you know I think we have to be prepared for you know velocity at all times and that's a good

[00:15:10] thing and obviously the job in the VC community is how do I how do I sort the the likely from the

[00:15:17] revolutionary from the impossible and you know and I don't do that work I focus specifically in how we

[00:15:24] provide better data access to users yeah you know but I do often like to use patterns or a metaphor

[00:15:30] to think about our role in the world and here in San Francisco one of the easiest metaphors to

[00:15:34] reach to is the gold mine era where we often talk about the difference between the gold miners

[00:15:42] and those that provided them picks and shelves and you know if we think about the future being

[00:15:48] difficult to predict I think there's this casey stangle right I never predict anything especially

[00:15:52] the future you know that we want to make sure that our product is an adoption vehicle for change

[00:16:01] and if you're a VC today number I should say the two most prominent letters that exist for you are

[00:16:07] AI and your big sort of question is where is AI going to impact enterprise what's going to be the

[00:16:14] killer application and what's the product that's going to enable that application and these are

[00:16:18] really hard questions to answer this is where prediction steps in what sigma does is provide the

[00:16:25] adoption vehicle for AI sigma is again the access point to users we are the access point to massive

[00:16:31] amounts of data which LLMs are predicated on that ML is predicated on so as we build more data

[00:16:39] science capability as we build more AI into the things that we do every day whether that is

[00:16:45] predicting inventory levels or trying to understand customer support engagement what sigma does

[00:16:53] is allow the evolution and the data to happen under the covers and that the expression of the AI

[00:16:59] can get to the end user we connect the spreadsheet user to the LLM we connect the data science

[00:17:05] ML model to the person asking a natural language query this trying to engage with an end customer

[00:17:12] so you know we think a lot about the fact that we add value directly to data but we equally is

[00:17:19] importantly provide a future proof for those that understand that we can't necessarily know what

[00:17:25] we're going to do with data with AI with ML or any other technology that comes along with the next

[00:17:31] few years right we want to know that we've provided ourselves the ability to take advantage of it

[00:17:36] when it comes to do that in a way that there's guarantee trust where there's verifiability

[00:17:43] and where there's access and this is exactly the platform that sigma has built.

[00:17:47] Another topic I'll have to explore with you today is the sustainable technological growth it's

[00:17:53] a topic of increasing in port and so one of the reasons I wanted to bring it up with you is when

[00:17:57] I was doing that little research on you before you came on the podcast today I saw in your

[00:18:02] discussion on the New York Stock Exchange for all talk that you touched upon how at sigma you also

[00:18:08] support sustainable tech growth it's a topic very close to your heart so can you just expand on

[00:18:14] on that and maybe discuss how companies can actually integrate sustainability into their data

[00:18:19] and analytics practices because I think it's something that a lot of business leaders want to do but

[00:18:23] getting it right that's that's where they need that helping him. You know I think that you know

[00:18:28] sustainability of course has many definitions and you know one of the I think the the simplest

[00:18:34] business definition for sustainability is and I afford to do this over the lot you know it's really

[00:18:40] becomes that simple and enterprise is you know just laden with complexity so I offer very simple

[00:18:48] definition as a first step for folks that are trying to be on this path and that is how do you

[00:18:53] make your individual employee more productive and that less tooling it's just that simple

[00:19:00] and I think the question that CIOs CFOs people across the enterprise wants no the answer to is

[00:19:07] how do I I'm paying a very I pay a lot of money to these individuals that show up every day with

[00:19:12] the best intentions to help my company improving compete but if I have to buy yet another product

[00:19:19] and somehow figure out how to manage it and integrate it secure it and govern it every time

[00:19:26] that there's a new opportunity that is not sustainable so how do I move from a world where I took lots

[00:19:32] of computing storage and put it on AWS or Microsoft Azure I would take lots of databases and put them

[00:19:37] on snowflake and data bricks what sigma's allowing companies to do is take lots of different departmental

[00:19:42] applications and consolidate them into one platform that is far more customizable that is far less

[00:19:48] expensive that is far easier to provide access to and that doesn't require costly integrations

[00:19:55] so we think a lot about the modern data stack really becoming a simpler architecture a more flexible

[00:20:03] architecture and a more accessible architecture over time so for any business leaders listening to our

[00:20:08] conversation today anywhere in the world that are navigating the modern data era trying to overcome

[00:20:14] the numerous challenges and opportunities along the way how are you at sigma proposing to

[00:20:19] address some of these challenges that they're currently encountering and what future developments

[00:20:24] can we expect from sigma in enhancing data analytics capabilities for users I appreciate

[00:20:29] you probably helped out how much you can share but any teasers you can share about how you're helping

[00:20:34] what we can expect in the future so I mean I think we can expect you know some

[00:20:40] we can expect things that range from doing the things we've always done better and more efficiently

[00:20:47] to doing things that we never thought we could do before sigma as I've said you know even throughout

[00:20:53] this this discussion you know we've taken some of the activities around looking at historical data

[00:20:59] which has been time consuming where we've always had middle people between our ask and the ability

[00:21:05] to get the data we need to make our decision based on our asks that sort of complexities going away

[00:21:10] and you should expect just continued focus on an end users ability to do their job independently

[00:21:17] at the same time when we look forward the idea that for example we can build novel applications

[00:21:23] on products like sigma build live on products like snowflake and data bricks that's something people

[00:21:30] haven't realized was possible we haven't a feature called an input table only product in the market

[00:21:36] that allows an end user to securely update the data warehouse so that they can in effect rate their

[00:21:43] own applications that is going to cause a significant rethink of the way that we do business today

[00:21:51] in our VC landscape a challenge our VCs to you know how do they manage there the companies that

[00:21:58] they're asset managers if you think about a portfolio company for a VC I'm going to bet that 99

[00:22:04] percent of the listening audience collects their quarterly results from those companies in a

[00:22:08] spreadsheet and then they somehow imported into software and they just take this for granted

[00:22:14] but the idea that companies can collaborate through sigma in real time and avoid that whatever

[00:22:22] for use asynchronous process is pretty revolutionary how about and then a portfolio company that

[00:22:26] just goes to a web page puts their quarterly results in and that automatically appears in your

[00:22:32] warehouse and all your formulas run and you give them immediate feedback as a result of that

[00:22:37] we have that happening today we have customers an inventory and supply chain management

[00:22:42] completely rethinking how they engage with their upstream and downstream customers

[00:22:47] because those customers no longer have to have sophisticated software to engage with them

[00:22:51] they don't need to send them a spreadsheet in order to update their inventory levels

[00:22:55] they could do that live and simply just in a web page that is a world in which people can

[00:23:03] radically improve productivity radically improve the velocity which they do their business

[00:23:08] radically improve accuracy so those are the sort of things that you can anticipate coming from

[00:23:13] sigma as sigma recognizes that as cloud evolved and as the cloud data warehouse came around

[00:23:21] that we should be rethinking applications and workflows altogether let's put a huge on it

[00:23:26] I have you on the podcast today so which gold in your answers and your insights that you're

[00:23:31] sharing with everybody and I've got to ask on a personal level whether it is in the workplace or

[00:23:36] in our personal lives as this almost real pressure on everyone to be in a state of continuous learning

[00:23:41] so a question I'd love to ask you is where or how do you self educate how do you keep up to speed

[00:23:47] with the non-stop technological change and everything in between anything you can share on how you

[00:23:54] keep up speed on the trends and everything first why I appreciate your gold reference coming up my

[00:23:59] metaphor that was that was good follow on you know one of the most fun things in my job I have

[00:24:07] two very diverse audiences that I get to talk to and learn from every day no no one is because we

[00:24:13] work across all these different types of companies listening to their problems their opportunities

[00:24:19] and how they see the world is the best education because it's not theoretical if you listen to a

[00:24:26] customer they're not thinking about what might be true what they might do or that they they're

[00:24:32] solving their problem today they're acting they act with urgency they engage us to help solve those

[00:24:38] problems and those companies range from healthcare companies to financial services to retailers and

[00:24:45] everything in between and that is just ton of fun that education that I get from customers not only

[00:24:53] informs our product and our company but you know obviously it just informs me in it and that's

[00:24:57] I find it fascinating at the same time I have one of the most fun things I do in my job aside from

[00:25:03] that is I meet everybody that joins the company we do a one-on-one when they when they start

[00:25:07] and it's important for me to do that not just because we want to build a great culture here and

[00:25:12] cultures predicated on on relationships but also because you want to talk to them when they join

[00:25:18] not when they've been here a year when they've been here a year they're sort of in culture

[00:25:21] aided they know what sigma knows but when they join here they're coming with ideas without

[00:25:26] really understanding sigma and so collecting all those diverse perspectives and thinking about

[00:25:31] their implications for us is a really really important and unique opportunity so you know I would

[00:25:37] say that we all have the ability to self-educate just by you know talking to the people that work

[00:25:43] with us and depend on us every day beautiful and I think that's a perfect moment to end our

[00:25:48] conversation today but before I do let you go for anyone listening wanting to find out more about

[00:25:54] sigma computing maybe explore the topic we've discussed today or in more detail or even contact

[00:25:59] you or your team or connect with you where would you like to point everyone listening well first of

[00:26:04] all you know it wouldn't be my my inner marketer says you definitely need to go to sigma computing

[00:26:09] dot on yeah but I also offer always my email address at palmer at sigma computing dot com I love to

[00:26:15] engage in these conversations and hear what people think I know that I only have a part of the

[00:26:22] view of what's going on in the world so going back to self-education I think those conversations are

[00:26:26] super important and then I would definitely encourage folks to engage with our various events whether

[00:26:32] they are webinars or the ones that we physically host with our partners like snowflake and data bricks

[00:26:37] out in the field we have some exciting regional events and of course there are the big summits coming

[00:26:43] up in June where you can hear a lot more from sigma well so much I loved from our conversation

[00:26:49] today and I think the big takeaway is making high quality decisions based on high quality data

[00:26:55] involves a combination of things like data awareness accuracy collaboration communication

[00:27:00] governance accessibility tools culture and a commitment to ongoing improvement and I think

[00:27:06] collectively these elements create that strong foundation for data driven decision making

[00:27:11] within organizations I do urge anybody listening to check out the website I'll put a link

[00:27:17] on the show notes so people can find you nice and easily but again

[00:27:21] and just thank you for sharing your insights with me to the

[00:27:24] was absolutely my pleasure it was a nice spent time I feel

[00:27:29] so as we wrap up today's conversation with Mike Palmer I think it's clear that the landscape

[00:27:34] of business intelligence and data analytics is not just changing it's almost undergoing a

[00:27:40] revolution and sigma computing stands out at the forefront of this transformation by breaking down

[00:27:46] barriers to data access and empowering businesses to leverage real-time collaboration forecasting and

[00:27:53] decision automation but it's that journey towards a data driven future that is filled with

[00:28:00] yes challenges but also opportunities and things like high quality data governance the

[00:28:06] complex the simplification of complex tools along with the development of new collaboration

[00:28:12] platforms it feels like it's just the beginning so as we look to the horizon one question remains

[00:28:19] though how will you or how will your organization adapt and embrace these advancements in business

[00:28:26] intelligence to help you drive growth and innovation in your organization as always I'd

[00:28:33] love to hear your thoughts on any of today's topics and how you see technology impacting your work

[00:28:39] your life and indeed world please share your thoughts and join the conversation as we continue

[00:28:45] to explore how technology solving real-world problems making complex tech accessible

[00:28:50] and adding value to both our businesses and lives and as always you can do that by just

[00:28:56] tech blog writer outlook dot com sliding into the dm's and LinkedIn twitter instagram just

[00:29:03] at nil chue's connect on there but don't just hit connect or follow send me a little message

[00:29:08] I'd love to hear from you but i'm afraid that's it for today so just thank you for listening as

[00:29:12] always and until next time don't be a stranger