From data to ROI: finally, a tool for Citizen Data Scientists.
In the last few years, predictive analytics has changed the rules for marketing professionals in every industry, and non-IT profiles must access and process TB of information to improve job performance and quality of analysis.
With vast amount of information available at their fingertips, analysts can now make informed decisions in a record time, adjust strategies and tactics to the actions of competition, and intercept customer patters in almost real time to tailor an offer to their ever-changing financial needs.
The data scientist of the early century needed a strong technical background to navigate its way through complex programming Python, and distributed computing solutions. Tomorrow’s data scientists is a citizen data scientist: one who can think in terms of data, and use business oriented solutions to manipulate vast amounts of information from his PC, without disrupting established processes.
There is a belief we are limited in our actions by the infrastructure: we wager that with the right tool, non-engineers can begin to transform the way they think about data and build robust predictive models.
Timi Suite changed the way business and technology interact to make the process simpler, smoother, and simply better for all.
The new generation of analysts, no matter their degree, has grown in a data world, thinks in terms of databases and understands that the social interactions are now digital (or is it, that the digital became the center of social interactions?). Still, traditional solutions are not tailored for this reality and require very skilled professional to complete the simplest tasks. Tomorrow’s professional, however, will need to be data savvy, as medicine, marketing, finance, journalism, and a whole lot of other professions are now surrounded by data and navigating this new ocean will be mandatory for all.
No programming: while programming logic is at the heart of data processing, our tools will not require analysts to write code, simply drag and drop the transformation tasks they wish to complete, and set a few parameters. This removes the strongest barrier to entry into analytics, and the less tech-savvy will see they can think in terms of data, and dive into the information age.
No giant servers: while it’s neat to have more computing power than NASA in a lab, most companies do not have access to giant servers, and it is impossible to let an entire team process TB of information on distributed servers. Timi runs on a laptop and can process billions of records without heavy investments.