As the third quarter of 2024 comes to a close, I wanted to take a look back at some of the many highlights and developments in the world of data, AI, and technology as a whole. As I have said many times in the past, technology moves at such a fast pace that if you blink you will be sure to have missed something. While some of the things I cover are too big to miss, I want to make sure that I capture the things that I find the most fascinating and relevant to today as well as share my thoughts on where things are headed. Today, we will be looking at a collection of 5 topics, stories, and releases that I hope you find as interesting as I do.
Starting off the list with the Gartner Magic Quadrant for Analytics and BI Platforms for 2024 (technically quarter 2. Don’t blame me, blame Gartner). I have been following this report for many years now and I think that this year has had the most changes of any year in that time. I think the biggest shift in this year’s report is the amount of leaders in the space. Microsoft, Salesforce (Tableau), and Qlik are no strangers to this category. However, ThoughtSpot makes its return to the space, as well as Oracle and Google. And you can also see that many Challengers and Visionaries are also right at the cusp of breaking into the Leaders section. Which doesn’t surprise me, as these companies have had many years to refine their platforms to provide a mature, comprehensive offering in the analytics space.
For the most part, the placement of the companies doesn’t surprise me much. With the amount of companies that are using Power BI, it makes sense to see Microsoft with a commanding lead. What did surprise me was Oracle being a leader. While Oracle is pretty much a household name, you don’t hear a lot of people using Oracle for their BI, analytics and reporting needs. I imagine this has to do with market presence and the companies that were polled by Gartner. Another surprise was that Sigma Computing didn’t make the cut. With the rise of query-based analytics, you would think that a company whose rapid momentum around spreadsheet-based analytics would be on there. Maybe next year.
Compared to some of the other reports in the industry, I do find generative AI to earn its weight in the report criteria. As business intelligence and analytics platforms are used by people of all skill levels, having greater self-service and content generation capabilities through the form of AI can increase report development speed and therefore cut down on BI request queues. This opens up more time for more use cases and the potential to explore untapped functionality in these tools. That being said, I highly recommend that you stay up to date on your BI platform’s releases (especially if you are not on SaaS) to make sure you are able to take advantage of the latest and greatest technology.
As always , I recommend that you read the report to understand the full evaluation criteria, especially if you are using it as part of your company’s evaluation.
If you’ve attended a data conference in the past couple of years, chances are you’ve walked by The Ravit Show at one of the booths. Hosted by Ravit Jain, the show covers a wide range of topics and gets new and emerging technologies in front of the show’s broad audience. In this video podcast, Ravit is joined by Mona Rakibe, Co-Founder & CEO of Telmai, to launch a new web series around data quality, a topic that was highly demanded by the community.
The inaugural episode was a fantastic roundtable with other digital leaders in the data quality and data product space. At this point you can probably guess what two letter acronym the conversation kept coming back too. Yup, AI. Data quality is such a foundational aspect to AI that it needs to be beaten over the head multiple times. I am not saying that sarcastically, we still see companies that try to use AI on top of bad data in a lake and warehouse that fail and go back to the drawing board. A quote that stood out to me on the panel was “…if you haven’t cleaned your house, it will be really difficult to do any type of AI or any kind of predictive analytics”.
Another thing that was interesting to hear discussed was enabling people with AI as it pertains to risk. Someone mentioned that you can go complete risk avoidance and just not give people access to data products and their tooling. But that is not a healthy long-term approach. Instead, risk management, as simple of a concept as it sounds, should be a priority with a proper plan in place.
I won’t spoil the rest of the episode but definitely check out this fantastic conversation. I have subscribed and will be waiting for the next episode of the data quality series to drop!
https://www.youtube.com/watch?v=yqQE_iB2RXQIn September, SME co-hosted a webinar with Revefi on end-to-end, generative AI-powered data observability. Revefi’s platform helps augment data teams with distinguished-level expertise in data architecture, system performance, optimization, and cost management. Their unique AI data engineer dubbed Raden helps ensure high-quality data, manage data pipelines, optimize spend, and boost operational efficiency as either an Autopilot or CoPilot. The webinar came hot off the press of the announcement of Raden as well as a Series A funding round for Revefi.
In the webinar, SME and Revefi explore some of the common challenges in the modern data observability landscape as well as the direct impacts to things like costs and efficiencies. Revefi also gave a first look demo of Raden. This webinar should be interesting to anyone that is a data engineer or plays a stakeholder role in the companies data warehouse or lakehouse solution. I highly recommend watching it to learn more!
https://www.smesgroup.com/genai-powered-end-to-end-data-observability-webinar
On July 19th, many people across the world found themselves experiencing major issues with their computers and servers. A defective sensor configuration update pushed out by cybersecurity firm Crowdstrike led to a global outage that lasted for several hours. The update, tied to Windows PC’s and Servers, caused major disruptions that spanned across many industries: including airlines, emergency services, and government. I am pretty sure everyone reading this was personally affected in one way or another.
This outage was a prime example of how reliant the world is on technology and how the of modern IT infrastructure can have widespread consequences when something goes down. If this wasn’t an advertisement for cybersecurity, I don’t know what is. While the actual issue was resolved in a couple of hours, many machines had to be updated manually which resulted in days before it was business as usual. The estimated financial impact of the event is at least $10 billion. Again, as we become more interconnected with technology, we need to anticipate and mitigate risks with a strong cybersecurity footprint across the entire enterprise.
https://www.techtarget.com/whatis/feature/Explaining-the-largest-IT-outage-in-history-and-whats-next
Has anyone ever told you to think before you talk? I am sure we got that a lot from our parents. Well, now generative AI is getting the same lesson. In September, OpenAI announced the preview of a new series of models “designed to spend more time thinking before they respond”. This so called “reasoning model” is named o1 (nicknamed Strawberry) and will be able to solve more complex problems, code better, and think more like a human would. And of course, with more value, comes a higher price tag. However, OpenAI is also releasing a “mini” version of o1 that is smaller, faster, and cheaper for applications that require reasoning without broad world knowledge.
One of the main benefits of the reasoning model is that it will be able to solve more problems in the fields of science and mathematics. I remember a year ago when someone showed me how generative AI could sometimes fail at simple math problems and was stunned. Honestly, that and the hallucinations were the main driver of my skepticism and apprehension to use it initially. But with updates like o1, we are moving towards a more human-like AI experience….for better or for worse. Looking at the pricing compared to standard OpenAI, users are expecting to pay 3 times more for input and 4 times more for output. Does that cost justify its usage for your use cases? Only time will tell but I do think this is a step in the right direction.
https://openai.com/index/introducing-openai-o1-preview/
While only a quarter of the year left, 2024 has been exciting and innovative in the world of tech. These topics and events were just a few of the many highlights that we experienced so far. I am optimistic that the rest of the year will continue to bring us new technological innovations, exciting breakthroughs, and new ways for us to increase productivity. I am always keeping my eyes and ears open to learn new things, so if you want to discuss these topics or maybe another topic that you find interesting, you can message me on LinkedIn or email me at gbarrett@smesgroup.com. I hope you had a great third quarter of 2024 and are ready to finish out the year strong!
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