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So, what you should have learned so far,
in this introductory lecture, is what big

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data is all about, what is web
intelligence, and what is big data

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analytics.
You should be able to answer simple

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questions that may arise in casual
conversations these days about any of

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these topics already.
To test your understanding, we have a

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small quiz.
So, please complete that quiz before

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Monday.
Last but not least, please remember to

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fill the survey questionnaire so that I
get to know all of you better.

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Before wrapping up the week, I'll give you
a preview of what's to come in the next

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few weeks.
The next week is all about search and

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finding stuff.
The basic elements of web search, page

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rank, and indexing will be covered next
week.

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Normally, this is not a part of what we
consider big data, or web intelligence.

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However, I feel it's really important to
understand how the web works, how big data

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and web scale is stored and can be easily
accessed because it's otherwise impossible

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to deal with other kinds of big data
unless one understands these basics.

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So, next week, we'll cover search and
indexing, ranking, and some relationships

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to human memory, which might be
interesting to some of you.

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Searching structured data using search
techniques rather than data base ones and

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then get into some slightly advanced
topics as well, in particular, object

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search, where we will study locality
sensitive hashing and touch upon

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associative memory.
Both topics very relevant to big data.

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At the same time, searching, indexing, and
ranking will be really warm-up exercises

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easier than the weeks that follow where
you'll get into little more Mathematics

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with machine learning and information
theory, followed by big data technology

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where we need to understand how databases
and distributed systems actually work.

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So, the next week might seem a little
easy-going to some of you, and probably

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will get many of you up to speed so that
you're able to handle the challenges of

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the following weeks.
So I look forward to see all of you next

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week for our first full-blown lecture.
See you then.