?? Want to stay ahead in AI? Work with startups. Big enterprises often struggle with AI adoption—not because they lack resources, but because their procurement processes are too slow to keep up with the pace of innovation. By the time they implement a solution, it’s already outdated. The best way forward? An experimentation mindset. In our latest Solid Journey blog, CTO & Co-Founder Tal Segalov breaks down: ?? Why enterprises need to “fail fast, scale fast” to stay competitive ?? What makes AI solutions truly scalable & impactful ?? Why startups are the perfect partners for AI-driven innovation ?? The takeaway? The companies that embrace agile, startup-led innovation will outpace those stuck in rigid procurement cycles. ?? Want insights like this delivered straight to your inbox? Sign up for the Solid Journey newsletter to stay ahead of the AI curve. Read the full post here ?? https://buff.ly/DBgR0fj Sign up for the newsletter in the comments ?? #AI #Startups #Innovation #DigitalTransformation #FutureOfWork
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Data democratization's next big leap.
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- 2024
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Solid - Analytics Workflow Management员工
动态
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? AI isn’t here to replace data analysts—it’s here to supercharge them. Too many companies focus on using AI just for automation when the real opportunity lies in enhancing human expertise. Instead of replacing analysts, AI should be redefining workflows, making it easier to uncover insights, improve accuracy, and scale impact. In this week’s Solid Journey newsletter, we explore: ?? How to align AI with business goals (beyond just efficiency) ?? Why workflow redesign matters—not just automating old processes ?? The real power of AI in analytics—boosting speed, scale, and quality ?? The key takeaway? AI is a strategic partner, not just a tool. When used right, it makes your data team more effective—not obsolete. Read the full edition here: https://buff.ly/4ildAJO #AI #DataAnalytics #Automation #FutureOfWork #DigitalTransformation
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?? Your data & analytics strategy is only as good as its alignment with your business goals. Too often, companies invest in data infrastructure without first defining the business outcomes they want to drive. The result? A sea of dashboards, fragmented systems, and insights that don’t move the needle. In this week’s Solid Journey newsletter, we break down a real-world example from a travel industry D&A leader: ?? A new CEO set clear, business-driven metrics (revenue per room, utilization) ?? The D&A team collaborated across business units to define analytics needs ?? They realized their fragmented data stack couldn’t support these goals—so they modernized it ?? The takeaway? Data strategy isn’t just about technology—it’s about aligning people, processes, and priorities. Want the full story? Read the latest edition here: https://buff.ly/43gdLlB #DataStrategy #Analytics #AI #DigitalTransformation #BusinessGrowth
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It's always great to get out and speak about a topic that's near and dear to our hearts - the future of data innovation! Thanks again to Tperson for having us.
Excited to have presented Solid - Analytics Workflow Management at the TPerson Data Leaders Meetup event today! TPerson, a full-stack data agency, hosted a fantastic discussion on the future of data innovation. My presentation focused on how Solid empowers data organizations to gain better visibility into their data assets, ensure consistency in analysis across different tasks and analysts, and ultimately boost team productivity. We explored how the real challenge for data leaders isn't just writing more SQL, but rather identifying the right data, reusing past work effectively, and bridging the gap between business needs and data language. I was also thrilled to join a panel discussion together with Aviad Harell, Elad Moskovitz, Orly Shoavi, Liad Itzhak and Ilan Kadar where we discussed the role of AI in data, and best practices data leaders need to adopt today. During the panel, we discussed the missing layer in many data stacks: a system for controlling, documenting, and understanding data structure – a "CRM for data." This would enable smarter workflows and AI augmentation. We also delved into the transformative potential of AI in the data world and how leaders should adapt. My key takeaway? Look ahead three years: what will data and analytics look like? Start implementing those changes now to gain a competitive edge through data efficiency. Huge thanks to Tperson for organizing such a meaningful and insightful event! #data #analytics #solid #AI #futureofdata
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In today’s AI-driven world, Chief Data & Analytics Officers (CDAOs) are stepping into the spotlight. They’re not just overseeing data—they’re driving revenue, shaping strategy, and redefining what it means to be a leader in the enterprise. We broke it all down in one of our most popular Solid newsletter editions. Swipe through the highlights ?? If this kind of insight is valuable to you, imagine having it delivered straight to your inbox every week. ?? Join hundreds of data leaders following our journey as we build an AI-powered analytics startup. ?? Read the full newsletter & subscribe here: https://lnkd.in/efyq93K3
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Solid - Analytics Workflow Management转发了
Imagine you're an analyst, and you are turning to your friendly neighborhood AI to help you find the right data to use to answer a business question. The good people who built that AI worked really hard to get it to provide the right result (see yesterday's post I made on the matter). The helpful, and well-intentioned, chatbot has provided you with an answer (see below). How do you know it's the right answer? How do you know if you can trust it? Is the AI hallucinating again? Is it being really confident about something that it's not 100% about? If it's not 100%, what percentage of confidence should it be? When you ask a colleague at work to help you find the right data asset to use, how confident are you of _their_ answer? Is the AI held to a different bar vs what a human is held to? Are AIs allowed to get things wrong at all?
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?? What does the modern data stack really look like in practice? After speaking with 200+ organizations, we’ve seen firsthand how cloud data warehouses like BigQuery, Databricks, and Snowflake have taken the lead—powering analytics at scale. At Solid, this isn’t just interesting—it’s actionable. It helps us focus our integrations and partnerships where they matter most. Our founder dives into the insights here ??—curious to hear what you think! What’s driving your cloud data warehouse decisions today? #DataAnalytics #ModernDataStack #BigData #BI
I know many of you hate pie charts... but, I do think it's a good use of one in this case. (feel free to comment ?? if you disagree and help me learn) We often mention at Solid that we've been interviewing people across the world to help us understand the right problem to solve, and the right way to solve it. More than 200 organizations actually. In many of those interviews, we also learn what cloud data warehouse the interviewee's company uses. (as well as BI platform, use of DBT, etc) As we're all about analytics, we decided to analyze this data. What we've learned, is that the top cloud data warehouses are leading the market by far, as far as analytics databases are concerned. 75% of those we spoke with are using Google's BigQuery / Databricks / Snowflake . Naturally, there's bias in our data - we only speak with those companies who want to speak with us, meaning they are looking to engage with startups and our initial pitch intrigues them. These are mostly companies in the 1,000-5,000 employee range, although many of them are much larger than that (even 20x-50x larger). For a startup, this is actually extremely helpful. We can focus our technical integration and GTM partnership efforts on a specific set of technologies and companies. On a broader level, this is also a very interesting observation, as we see technologies that didn't exist 15 years ago being the vast majority of the respective market. What are your thoughts on this? Would love to hear them in the comments below. Solid - Analytics Workflow Management
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?? We're running a Data Viz Contest ?? We're officially announcing our Data Visualization contest for February! Full details in the attached document. What’s at stake? ? REAL Prizes for 1st, 2nd, and 3rd place that will propel your career growth! ? Bragging rights as a GOATs Visualization Champion ?? ? Showcasing your work in the Community The Details: ?? You must join our free GOATs LinkedIn Group (link in the comments) ?? Any visualization tool can be used (Tableau, Power BI, Excel, etc.) ?? Submissions due by Friday, Feb 28th, 5:00 PM Pacific Time (US) ?? Judged on: Completeness, Creativity, and Readability by our panel of judges ?? Full contest details & submission guidelines attached (and in comments). Are you ready to flex your data viz skills? Comment below if you’re IN, and tag a fellow analyst who should join the challenge! ???? #DataVisualization #Analytics #GOATsCommunity #DataViz #CrimeData #LAPD #Contest #Tableau #PowerBI #Python #Excel
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How does your organization measure success? Learn more about how we're thinking about it in a recent newsletter we sent out written by Tali Hirsh. Read it and subscribe below ?? https://lnkd.in/eVhRHXDs
Success = 5VU2 - 2C - T It's a formula we came up with as we were looking to put together a framework representing the knobs/levers we can work on to improve our success. It applies both to the success of working with a discrete customer, as well as the broader potential market. V (Value): Does our product provide undeniable value to analysts and their managers? If the pain we solve isn’t big enough, customers won’t care. U (Urgency): Do they need it right now? Urgency is the most critical factor, which is why it’s squared. If there’s no pressure to act, the deal will drag forever. C (Complexity): Is the solution too overwhelming? If it’s too complex to adopt, people won’t engage. We needed to simplify how we presented our product. T (Time commitment): How much effort does the customer need to invest before seeing value? The more time we required upfront, the harder it was to close deals. More detail on how we came up with this, and what we used it for, in Tali Hirsh's recent blog post: https://buff.ly/40NWMnM
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It’s always a great time when the team is together in person.
This week I'm visiting our Israeli R&D office. We've built an amazing team - like a commando unit. The market is showing a huge amount of excitement around our product, and we're just getting started! (Whiskey helps create better code, btw) Tal Segalov Alon Ashkenazi Maya Bercovitch (Liani) Tali Hirsh Raed Awad Dana Yaniv Gil Zalcberg Ben Menahem Areen Nser Atwa Ibrahem Igbaria Dalia Khateb Evyatar Malka Dikla Avigad Wingarten Michal H. Tzlil Vigdor Solid - Analytics Workflow Management
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