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Laboratory Informatics 101
Deﬁnitions and Purpose

The Name
Application of IT, statistics, and
BioInformatics information theory to biological
inquiry

The Name
Application of IT, statistics, and
BioInformatics information theory to biological
inquiry

ChemInformatics

The Name
Application of IT, statistics, and
BioInformatics information theory to biological
inquiry

Application of IT, statistics, and
information theory to chemical
inquiry
ChemInformatics

Laboratory Informatics

Application of information technology,
theory, and statistics to Laboratory
Management

How Exactly?
Information
Technology
-Databases

-

How Exactly?
Information
Technology
-Databases
-Applications

-

How Exactly?
Information
Technology
-Databases
-Applications
-Servers

-

How Exactly?
Information
Technology
-Databases
-Applications
-Servers
-Bench/Desktop Computers

-

How Exactly?
Information
Technology
-Databases
-Applications
-Servers
-Bench/Desktop Computers
-Storage

-

How Exactly?
Information
Technology
-Databases
-Applications
-Servers
-Bench/Desktop Computers
-Storage
-Networks

-

How Exactly?
Information
Technology
-Databases
-Applications
-Servers Information
-Bench/Desktop Computers
-Storage Theory
-Networks

-

How Exactly?
Information
Technology
-Databases
-Applications
-Servers Information
-Bench/Desktop Computers
-Storage Theory
-Networks
-Compression Algorithms

-

Key Systems

• Instrument Systems
• Scientiﬁc Data Management Systems
• Electronic Laboratory Notebooks
• LIMS

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The Briefing Room with Krish Krishnan and Teradata Live Webcast on Dec. 4, 2012 The current Holy Grail of analytical systems is the Unified Data Architecture: a management layer that connects people and systems to all the appropriate information sources, both structured and unstructured, across the entire enterprise. The idea is to provide a strategic view of information assets, ideally with an intelligent metadata layer that helps users align salient data sets, thus enabling a big-picture perspective that fosters insight, collaboration and improvement. Check out this episode of The Briefing Room to hear veteran Analyst Krish Krishnan explain why we're closer than ever to achieving this holistic perspective for data assets. He'll be briefed by Imad Birouty of Teradata, who will tout his company's Unity offering, a management environment for connecting Teradata systems of all shapes and sizes. He'll explain how Unity allows users to navigate through complex information architectures, route queries to specific data sources, even access Big Data in Hadoop via AsterSQL. Birouty will also offer a sneak peek at Shark, a new project spun out of the Kickfire acquisition, which promises super-high performance queries on specific workloads. Visit: http://www.insideanalysis.com

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Learn more about it here: https://www.youtube.com/watch?v=6mSg6ij0Fak Albert presents how effectively gather functional requirements for sensor data analytics, which aspects are the most important for designing IoT data platform and which steps needs to be taken to implement such solution to gain great return on investment. Watch our webinar about profit from IoT: https://www.youtube.com/watch?v=6mSg6ij0Fak&t=3s If you would like to read something more about IoT, please do not hesitate to download our white paper "Data Analytics for Industrial Internet of Things": https://getindata.com/blog/white-paper-big-data-analytics-industrial-internet-things/ Speaker: Albert Lewandowski Linkedin: https://www.linkedin.com/in/albert-lewandowski/ ___ Getindata is a company founded in 2014 by ex-Spotify data engineers. From day one our focus has been on Big Data projects. We bring together a group of best and most experienced experts in Poland, working with cloud and open-source Big Data technologies to help companies build scalable data architectures and implement advanced analytics over large data sets. Our experts have vast production experience in implementing Big Data projects for Polish as well as foreign companies including i.a. Spotify, Play, Truecaller, Kcell, Acast, Allegro, ING, Agora, Synerise, StepStone, iZettle and many others from the pharmaceutical, media, finance and FMCG industries. https://getindata.com

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The presentation has many use cases covering the following Image classification: "The process of identifying and detecting an object or a feature in a digital image or video," the report states. In retail, deep learning models "quickly scan and analyze in-store imagery to intuitively determine inventory movement." Voice recognition: "The ability to receive and interpret dictation or to understand and carry out spoken commands. Models are able to convert captured voice commands to text and then use natural language processing to understand what is being said and in what context." In transportation, deep learning "uses voice commands to enable drivers to make phone calls and adjust internal controls - all without taking their hands off the steering wheel." Anomaly detection: "Deep learning technique strives to recognize abnormal patterns which don't match the behaviors expected for a particular system, out of millions of different transactions. These applications can lead to the discovery of an attack on financial networks, fraud detection in insurance filings or credit card purchases, even isolating sensor data in industrial facilities signifying a safety issue." Recommendation engines: "Analyze user actions in order to provide recommendations based on user behavior." Sentiment analysis: "Leverages deep learning-heavy techniques such as natural language processing, text analysis, and computational linguistics to gain clear insight into customer opinion, understanding of consumer sentiment, and measuring the impact of marketing strategies." Video analysis: "Process and evaluate vast streams of video footage for a range of tasks including threat detection, which can be used in airport security, banks, and sporting events."

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Li101 definitions and purpose

1. Laboratory Informatics 101 Deﬁnitions and Purpose

2. The Name

3. The Name BioInformatics

4. The Name BioInformatics

5. The Name Application of IT, statistics, and BioInformatics information theory to biological inquiry

6. The Name Application of IT, statistics, and BioInformatics information theory to biological inquiry ChemInformatics

7. The Name Application of IT, statistics, and BioInformatics information theory to biological inquiry ChemInformatics

8. The Name Application of IT, statistics, and BioInformatics information theory to biological inquiry Application of IT, statistics, and information theory to chemical inquiry ChemInformatics

9. Laboratory Informatics

10. Laboratory Informatics

11. Laboratory Informatics Application of information technology, theory, and statistics to Laboratory Management

12. How Exactly? -

13. How Exactly? -

14. How Exactly? Information Technology -

15. How Exactly? Information Technology -Databases -

16. How Exactly? Information Technology -Databases -Applications -

17. How Exactly? Information Technology -Databases -Applications -Servers -

18. How Exactly? Information Technology -Databases -Applications -Servers -Bench/Desktop Computers -

19. How Exactly? Information Technology -Databases -Applications -Servers -Bench/Desktop Computers -Storage -

20. How Exactly? Information Technology -Databases -Applications -Servers -Bench/Desktop Computers -Storage -Networks -

21. How Exactly? Information Technology -Databases -Applications -Servers -Bench/Desktop Computers -Storage -Networks -

22. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -

23. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -

24. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -Artiﬁcial Intelligence -

25. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -Artiﬁcial Intelligence -Business Process Modeling and Improvement -

26. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -Artiﬁcial Intelligence -Business Process Modeling and Improvement -Decision Support/Business Intelligence -

27. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -Artiﬁcial Intelligence Statistical -Business Process Modeling and Improvement Methods -Decision Support/Business Intelligence -

28. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -Artiﬁcial Intelligence Statistical -Business Process Modeling and Improvement Methods -Decision Support/Business Intelligence -Control Charts -

29. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -Artiﬁcial Intelligence Statistical -Business Process Modeling and Improvement Methods -Decision Support/Business Intelligence -Control Charts -Models -

30. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -Artiﬁcial Intelligence Statistical -Business Process Modeling and Improvement Methods -Decision Support/Business Intelligence -Control Charts -Models -Outliers, Means, Medians, other basic statistics -

31. How Exactly? Information Technology -Databases -Applications -Servers Information -Bench/Desktop Computers -Storage Theory -Networks -Compression Algorithms -Artiﬁcial Intelligence Statistical -Business Process Modeling and Improvement Methods -Decision Support/Business Intelligence -Control Charts -Models -Outliers, Means, Medians, other basic statistics -

32. Key Systems • Instrument Systems • Scientiﬁc Data Management Systems • Electronic Laboratory Notebooks • LIMS

Li101 definitions and purpose

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