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Cheap DATABASE AND BUSINESS INTELLIGENCE Scheduled Training Courses
KN3 offer cheap, reduced prices on scheduled Database and Business Intelligence computer training certification courses in key locations around London and the UK.
A comprehensive range of courses are available.
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Business Intelligence (BI) systems are the heart of any company’s analytical capability. This course introduces the delegate to all the necessary terminology, architectures, approaches, skills, techniques, and infrastructure necessary to design and implement a successful BI system. The course focuses on the generic skills that are necessary to create an effective BI system and will teach you the skills that underpin good BI development no matter which software platform you use.
A BI system has the potential to revolutionise your business. It can turn the mass of data that sits in your operational systems (Finance, HR, Sales etc.) into high quality, well-defined information. This information allows you to move from a ‘gut-feel’ approach of decision making to a proper, evidence-based approach. A well-designed BI system collects the appropriate data from your operational systems and move it into a data warehouse. There it is restructured and organised for analytical purposes and often deployed to data marts. The approach, methodology and design techniques required to build a BI system differ significantly from those required to build operational systems and include ETL (Extract, Transform and Load), dimensional modelling and OLAP (On-Line Analytical Processing). Target Audience:
This course is made up of a mix of theory and vendor-neutral practicals that allow delegates to apply the principles they have learnt. It is ideal for developers, software engineers, database administrators, data analysts, system analysts or application designers who will be involved in designing, building or maintaining a BI system. Please note delegates who have previously attended CSWARDE2 - Effective Data Warehouse Construction should not attend this course. .. more here
Dimensional modelling is an integral part of any BI (Business Intelligence) system and can be used within the data warehouse and/or the data marts. This 3 day course assumes no prior knowledge of dimensional modelling. It starts by discussing what a data warehouse is, how they are designed and the part that dimensional modelling plays. The vitally important process of requirement gathering is covered and attendees are shown how to:
- Collect the analytical requirements of the business users
- Create a logical model of these requirements
- Create a star schema from those requirements
Introduction to Data Science and mathematical models underpinning Big Data Technologies. Deep introduction to working with range of big data tools.
Target AudienceFor existing python developers and data analysts looking to up-skill into big data. .. more here
Fundamentals of Data Science is a three day overview course which blends discussion and group exercises to explore the field of data science with applied real world examples and projects. Teaching begins with a conceptual introduction to science, data science, big data and machine learning; followed by a litany of real-world data science and machine learning examples. The remainder is divided into two parts: python-illustrated and r-illustrated. After introducing both languages, the modules cover various applied topics (data preparation, statistics, Markov chains, neural nets) with examples in either python or R. .. more here
Introduction to R and data analytics. Deeper Introduction to Machine Learning.
Target AudienceAimed at people with existing technological and mathematical background looking to get a quick exposure to mathematics and techniques of Machine Learning. .. more here
Introduction to R, and broad coverage of mathematics for Data Science and Machine Learning: algebra, linear algebra, calculus, probability and statistics.
Target AudienceAimed at fledging data scientists who wish to have a proper understanding of the underlining mathematics and algorithms behind Machine Learning and data analytics. .. more here
Introduction to Python, Data Science and Big Data. Deep introduction to major Big Data technology for practitioners working with them.
Target AudiencePractitioners of data analysis and fledging data scientists who wish to leverage Big Data technologies such as NoSQL databases, Hadoop and Spark. .. more here
Introduction to Statistics, R, Python, Analytics, Data Science and Machine Learning. Sets up practitioners with working knowledge of whole field of data science, along with immediate practical knowledge of key analytical tasks.
Target AudienceFor fledging data science practitioners, and for IT professionals who wish to move to the exiting world of data analytics and machine learning. .. more here
Introduction to R and Python programming languages. Deep coverage of mathematics, algorithms and technology of Machine learning.
Target AudienceThis course is aimed at fledging Machine Learning practitioners, and data analysts who wish to gain more in depth knowledge of Machine Learning. .. more here
Both Data Science and Big Data have risen to prominence recently. Whilst they are not immutably linked, it is certainly true that many data scientists work extensively with big data. Both topics are so new that they are poorly understood; nevertheless there is considerable interest in both and there is a significant shortfall in the number of trained data scientists in the job market. This course introduces both the job role of the data scientist and will help develop familiarisation with big data. The course is vendor neutral; it is not about how to use any vendor's products, it is about the fundamental underpinnings of these two important subject areas.
This course is intended for people aspiring to be data scientists and/or to work with Big Data. Others who may take this course include Business Intelligence (BI) professionals who want to work with big data and/or are looking to move into Data Science. People coming into the course are expected to have at least 3 years experience working in the IT field—typically in the areas of databases, BI, analytics or related areas.. more here
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