Data science as a service has been progressively changing areas like business optimisation, artificial intelligence, media monitoring, retail, and everything you can think of. All organizations manage and operate different types and amounts of data.

But it all comes down to how you manage your data if you are to optimise your business model.

Good strategies for data understanding and setup have proven important because your data contains the keys to managing your company’s most valuable assets. But one must keep in mind that data collection on its own gives little business insights value.

How data science as a service (DSaaS) is helping business?

To get value from massive data and meet business objectives, one needs expertise, tools, and knowledge to comprehend what questions to ask and how to reveal the right patterns in the data. As well as the skills to create useful models.

Nowadays, despite being considered successful, many companies are still not reaping the advancement and benefits they could from data science solutions.

There are not many industries that have the support and opportunity to develop these competencies within organizations. They often struggle to gather the set of talents able to perform advanced analytics and generate insights from all the information they have amassed.

The question facing every company today, be it a start-up, non-profit or project site that wants to attract a community, is how to use data effectively — not just their own data, but all the available and relevant data out there.

Using it effectively requires something different from traditional statistics, where actuaries in business suits perform arcane, but fairly well-defined kinds and methods of data preparation and analysis.

Data science vs. statistic: What is the difference?

What differentiates data science from statistics is that it represents the development of a more broad and holistic approach to the task at hand.

Extracting the true insights from data could help organizations obtain better business intelligence and play a major role in their field, ensuring competitors would not be getting more out of it.

That is why it is becoming an essential requirement for such organizations to leverage Data Science as a Service (DSaaS) systems in order to be able to transform their business and enhance their business operations’ competitiveness. This could vary from simple data automation platforms to complex big data platforms, such as our data delivery platform, Kaspian.

Choose the right Data Science Service Provider

To make sure you get the maximum output with minimum input when employing data science as a service company, it is important to make the right choice for a data provider after thorough consideration.

The kind of DSaaS we offer at Identrics, for example, is an award-winning model, which significantly accelerates your progress towards production-ready AI projects. What makes this possible is the fact that our data science team has a customised approach when it comes to text data.

We make sure to cover all the related tasks that an organization could be faced with regarding text data within a new data science project. The scope of our data science services includes data gathering and annotation; data analysis and processing; machine learning services and data transformation; and data visualization and communication.

We believe that not everyone needs to be a data scientist or an expert in everything. Whether in personal life or business, individuals, and businesses should invest in finding their area of competence. This is where our value comes from.

We specialize in our field and rely on your competence in yours, to reach the most appropriate solution to your data science goals. Our expertise includes all types of text classification, understanding, analysis, and generation, and we offer it as our Data Science on Demand service.

We are unique in the fact that we do not offer piecemeal information. Rather, we specialize in bundled pipeline services that give a global picture of the needed information with all the insights already extracted.

In addition to our text services which we skilfully combine and ensemble in pipelines according to our customers’ needs, we also weave custom logic, analytics, and machine learning models’ algorithms into them. We call the customised approach to each business with these steps, “Research on Demand.”

Explore our case studies

If you are interested in finding out more about the real-life success that our clients had with our solutions, make sure to have a look at the case study section on our website.

If you want to find out more learn more about how our solutions can help your business grow, contact us with your specific inquiry today!