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By Christian Buckner, Senior Vice President, Altair
Anyone who has been following the news in the data analytics and artificial intelligence (ai) market knows that there have been considerable changes in recent years. Large analytics companies like Alterix and Chart They have been the subject of mergers, acquisitions and privatizations.
The rise of open source language has put pressure on critical analytics technologies like SAS. Startups have burned a lot of money and learned hard lessons, sometimes without even achieving sustainable business models. And of course, the rapid adoption of generative ai has everyone wondering if they are doing everything they can to keep up with the competition. In short, there has never been so much uncertainty in data analysis.
As a result, it is more important than ever to think long-term about the analytics partnerships you forge. Are you choosing technologies that will stand the test of time? Are you choosing companies with proven track records? What do costs look like on the largest scales? How should my team grow as my data usage increases? Can my partners help me when things get tough? These have always been important questions when making decisions about analytics alliances, but in today's ever-changing landscape it is especially important to think about the future.
What to look for in data and artificial intelligence technology
Let's start with the technology side. With so many changes in the market, more providers in a data delivery workflow means more risk. Small, specialized software vendors that satisfy only one link in the chain typically have two outcomes: either they succeed and are eventually acquired by a company with a broader offering, or they never reach escape velocity. Either way, the result for you is disruption.
Instead, organizations should look for data and ai technology that run the gamut and can get the job done from start to finish. On the technology side, organizations should look for companies that offer everything, including:
- Data preparation
- Extract, Transform and Load (ETL)
- AutoML, automatic forecasting and automatic feature engineering
- Fine-tuning generative ai
- Development model
- Workload Orchestration
- Data visualization
- Analysis in multiple languages (including Python, R, SQL, and SAS language)
Additionally, when all of these tools are offered by the same technology partner, they are likely to come together much more naturally and elegantly. This means you don't have to spend half your time improvising tools, and when your data workers multitask, they don't have to jump from tool to tool trying to put together the workflow themselves.
“If you want your data solutions to stand the test of time, make sure your data providers have stood the test of time.”
The icing on the cake is a software partner that can deliver all of these things, deliver them in a streamlined workflow, and deliver them in a way that empowers both those with specialized data skills and those without. That way, the data team doesn't have to do everything. No-code and low-code tools allow stakeholders outside of the data team to tackle the small but important tasks that make up 80% of a data team's work, while freeing up the data team to tackle the bigger projects. difficult ones that require serious data science.
Ideally, the same partner can provide the complete package. End-to-end, seamlessly integrated, no code to code first. These are the hallmarks of frictionless ai and strong technology partners.
What to look for in data and artificial intelligence business approaches
However, technology is only half the battle. Many organizations have great technology, but do not project stability. Especially on the business side, when looking for a partner to address their data analytics and ai needs, leaders and organizations should prioritize companies that demonstrate proven results and stability.
Data is everything for today's cutting-edge organizations. Disruptions and miscommunications caused by unstable partners are unacceptable delays that jeopardize both short- and long-term success. If you want your data solutions to stand the test of time, make sure your data providers have stood the test of time.
Additionally, you can minimize uncertainty in your day-to-day life by partnering with an organization that has deep expertise in the field and a proven track record of world-class customer service. Partners are supposed to be just that: partners, not mere suppliers. You want someone who will be by your side to help you when things get tough.
Lastly, market uncertainty means everyone will be worried about prices and value. Prioritize partners whose business model and licensing system is designed for customers; You'll know them when you see them. You want to find a partner that will provide you with more value the more you use their offerings.
Want to learn more about how to navigate today's data and ai market filled with uncertainty? Make sure you attend Altair for free Future.Industry 2024 virtual eventwhere industry experts converge to discuss the future of frictionless data and ai.
Christian Buckner is senior vice president of data analytics at Altair. She has dedicated her decades-long career to helping innovative organizations build a better future by elevating data in decision-making and automation.
