Who is a Data Strategist, what he does and why he is necessary for a business, how Data Strategist differs from Data Scientist and Data Analyst, what knowledge has this IT-specialist and how much he is payed?
ETL, OLAP, OLTP, storefronts and data warehousing: what it is, why it is necessary and how it is connected with analytics and Big Data technologies. Read in a new article which factors are critical when choosing an ETL system and why even expensive industrial solutions will not save Data Analyst from all the problems of collecting and analyzing business information.
What is NLP and what does Data Science have to do with it, how does ML help analyze texts and predict the future, why deep learning has become so popular today. Read in a new article how artificial neural networks of the BERT type are arranged and when they can get ahead of a person in the tasks of processing natural language.
3 ways to make money on data relevant to any business. What information about their users can be profitably sold to the data exchange and how to do it legally, without violating the requirements of Roskomnadzor and GDPR. Who and why sells / buys user data - a brief overview of the market for data providers in Russia and abroad.
Why 85% of Big Data projects are doomed to failure and how to launch a successful data analytics project involving a freelance consultant are practical recommendations for the business.
Why Data Science is more than just analyzing information, how Data Scientist differs from Data Analyst, in which cases and for which business needs both of these professionals
Putting up of money in ML - inputs or investment? Estimating the effectiveness of using Machine Learning on the example of Churn Rate Prediction.
What is Customer Journey Map (CJM), why CJM is needed, how to build it and where to use - approaches and ways of developing CJM: analytical review, advantages and disadvantages, examples.
How to build CJM based on the computer website analysis of user behavior with the help of text clustering task
How to determine the category of a potential customer by his behavior on the site using machine learning and expert knowledge
When, to whom and why is Chief Data Officer required, where to find and how to employ such Top-manager and how much to pay him
