How to Write an Effective Executive Summary

Processual archaeology (formerly, the New Archaeology) is a form of archaeological theory that had its genesis in 1958 with the work of Gordon Willey and Philip Phillips, Method and Theory in American Archaeology, in which the pair stated that “American archaeology is anthropology or it is nothing” (Willey and Phillips …

High-level… The maximum amount of level, that’s what you wanted and so I put in the maximum amount of work for a top notch piece of advice. If you wanted a few short sentences then that would be low-level! Apparently I was wrong. High-level does indeed mean “a brief summary”.

1. Executive summaries should include the following components:
2. Write it last.
3. Capture the reader’s attention.
4. Make sure your executive summary can stand on its own.
5. Think of an executive summary as a more condensed version of your business plan.
6. Include supporting research.
7. Boil it down as much as possible.

High-level describe those operations that are more abstract in nature; wherein the overall goals and systemic features are typically more concerned with the wider, macro system as a whole.

A “high-level overview” is one that doesn’t cover details. It provides a very basic and general explanation or presentation of the material/subject. If you’re up in an airplane, what you see are only the big things, you have a perspective from a high level.

High-level tends to leave out details, low-level gets down into the details. This is a high-level summary of the other answers which went down into much lower levels of detail. OOH, there is the phrase “high level of detail” which means, of course, that you are discussing all of the low-level details, and vice versa.

The main difference between high level language and low level language is that, Programmers can easily understand or interpret or compile the high level language in comparison of machine. High level language is less memory efficient. Low level language is high memory efficient.

entire system

There are mainly three levels of data abstraction:

• Internal Level: Actual PHYSICAL storage structure and access paths.
• Conceptual or Logical Level: Structure and constraints for the entire database.
• External or View level: Describes various user views.

How to implement encapsulation in java: 1) Make the instance variables private so that they cannot be accessed directly from outside the class. You can only set and get values of these variables through the methods of the class. 2) Have getter and setter methods in the class to set and get the values of the fields.

Physical level: The lowest level of abstraction describes how a system actually stores data. The physical level describes complex low-level data structures in detail. Logical level: The next higher level of abstraction describes what data the database stores, and what relationships exist among those data.

The three levels present in this architecture are Physical level, Conceptual level and External level.

Physical data independence helps you to separate conceptual levels from the internal/physical levels. It allows you to provide a logical description of the database without the need to specify physical structures. Compared to Logical Independence, it is easy to achieve physical data independence.

Logical data independence: The ability to change the logical (conceptual) schema without changing the External schema (User View) is called logical data independence. Physical data independence: The ability to change the physical schema without changing the logical schema is called physical data independence.

The main difference between logical and physical data model is that logical data model helps to define the data elements and their relationships, while physical data model helps to design the actual database based on the requirements gathered during the logical data modelling.

Physical data independence is the power to change the physical data without impacting the schema or logical data. For example, in case we want to change or upgrade the storage system itself − suppose we want to replace hard-disks with SSD − it should not have any impact on the logical data or schemas.

A logical data model or logical schema is a data model of a specific problem domain expressed independently of a particular database management product or storage technology (physical data model) but in terms of data structures such as relational tables and columns, object-oriented classes, or XML tags.

The components of a logical data model include Entities, Relationships, and Attributes. Each Entity represents a set of persons, things, or concepts about which the business needs information. Each Relationship represents an association between two entities.

A database schema is the skeleton structure that represents the logical view of the entire database. Logical Database Schema − This schema defines all the logical constraints that need to be applied on the data stored. It defines tables, views, and integrity constraints.

Schemas are used in logic to specify rules of inference, in mathematics to describe theories with infinitely many axioms, and in semantics to give adequacy conditions for definitions of truth. …

Examples of schemata include rubrics, perceived social roles, stereotypes, and worldviews. The concept of schema was first introduced into psychology by British psychologist Frederic Bartlett in Remembering: A Study in Experimental and Social Psychology (1932).

Types

• Person schemas are focused on specific individuals.
• Social schemas include general knowledge about how people behave in certain social situations.
• Self-schemas are focused on your knowledge about yourself.
• Event schemas are focused on patterns of behavior that should be followed for certain events.

As nouns the difference between scheme and schema is that scheme is a systematic plan of future action while schema is an outline or image universally applicable to a general conception, under which it is likely to be presented to the mind.

Frederic Bartlett

Plural. schemes. The plural form of scheme; more than one (kind of) scheme.