Why Data Science as a Service (DSaaS)?

Data has been progressively changing areas like business optimization, media monitoring, retail, and everything you can think of really. All organizations manage and operate different types and amounts of data. 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 – data on its own gives little value.

To get value from massive data, 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.

Despite the success story of its service, many companies are still not reaping the advancement and benefits they could from Data Science. There are not many industries that have the opportunity to develop these competencies within organizations. They often struggle to gather the set of talents able to generate strong analysis and 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 of analysis.

Data Science vs. Pure Statistic

What differentiates Data Science from pure Statistics is that it represents a more broad and holistic approach to the task at hand. Data scientists are involved with gathering data, processing and rendering it into a tractable form, making it tell its story, and presenting that story to others. Extracting the true insights from the 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) in order to be able to transform its business and enhance its competitiveness.

DSaaS gives companies the chance to gain a data-driven advantage – the key to being more efficient and effective than opponents – without the costs of building a large team of data scientists and infrastructure in-house from scratch.

The Kind of DSaaS We – at Identrics – Offer

We employ a DSaaS model which significantly accelerates your progress towards production-ready AI. What makes this possible is the fact that our team knows it all when it comes to TEXT and we cover all the related tasks that an organization could be faced with regarding text data – data gathering and annotation; data analysis and processing; machine learning and data transformation; data visualization and communication.

Not everyone needs to be an expert in everything. This is the same across all industries. We specialize in our field and rely on your competence in yours, to reach the most appropriate solution to your data challenges. 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 customer’s needs, we also weave custom logic and algorithms into them. This is as easy for us as a child’s game, and we call it Research on Demand.

Success Story from the Risk & Compliance industry

Identrics RandC Case Study Image

In a series of posts, we would like to share some real stories that we have had with our customers, building together with their own solutions.

Download our success story from the Risk and Compliance industry: Filtering media content and alerting about the appearance of special interested entities:

Coming up NEXT:

Success story from the Media Monitoring industry: Media Monitoring Alerts and Reports

Оur client wanted to receive periodic alerts and a structured daily summary of all news on specific topics that cаme out in the region of several countries where the organization operates. The next post will show you how we combined Document Similarity, Named Entity Recognition, Sentiment Analysis, Abstractive Summarization, and much more to solve another data challenge. Stay tuned!