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googleが定義するところのアナリストについて

• dataとは?
  • words
  • 事実のコレクション

A

• Action-oriented question
  • A question whose answers lead to change
• Algorithm
  • A process or set of rules followed for a specific task
• Analytics skills
  • The qualities and characteristics associated with solving problems using facts
    • curiosity
    • understanding context
    • technical mindset
    • data design
    • data strategy
• Analytical thinking
  • The process of identifying and defining a problem, then solving it by using data in an organized, step-by-step manner
• Attribute
  • A characteristic or quality of data used to label a column in a table
• A technical mindset
  • The analytical skill that involves breaking processes down into smaller steps and working with them in an orderly, logical way
• Analytical thinking
  • Analytical thinking involves identifying and defining a problem, then solving it by using data in an organized, step-by-step manner.
• Analyze phase of the data life cycle
  • 最後のエンドポイントのこと、preprocessing等は含まない

B

• Big data
  • Large, complex datasets typically involving long periods of time, which enable data analysts to address far-reaching business problems
• Business task
  • The question or problem data analysis answers for a business

C

• Context
  • The condition in which something exists or happens
• Correlation
  • Correlation involves being able to identify a relationship between two or more pieces of data. A correlation is like a relationship.
• Continuous data
  • Data that is measured and can have almost any numeric value

D

• Dashboard
  • A tool that monitors live, incoming data
• Data design
  • Analytical skills that involve how you organize information
• Data-driven decision-making
  • The process of using facts to guide business strategy
• Data strategy
  • The analytical skill that involves managing the processes and tools used in data analysis
  • これには人の側面を含む
• Data analyst
  • someone who collects, transforms, and organizes data in order to drive informed decision-making
• Data science
  • a field of study that uses raw data to create new ways of modeling and understanding the unknown
• Data visualization
  • The graphical representation of data
• Data ecosystem
  • The various elements that interact with one another in order to produce, manage, store, organize, analyze, and share data

F

• Fairness
  • A quality of data analysis that does not create or reinforce bias

G

• Gap analysis
  • あるべき姿と現状の姿を分析すること
  • 結論を導き出し、予測を行い、情報に基づいた意思決定を推進するためのデータの収集、変換、および編成
  • A method for examining and evaluating the current state of a process in order to identify opportunities for improvement in the future

M

• Metric
  • A single, quantifiable type of data that is used for measurement
• Metric goal
  • A measurable goal set by a company and evaluated using metrics
• Measurable question
  • A question whose answers can be quantified and assessed

O

• Observation
  • The attributes that describe a piece of data contained in a row of a table
• Ordinal data
  • Qualitative data with a set order or scale
• Ownership
  • The aspect of data ethics that presumes individuals own the raw data they provide and have primary control over its usage, processing, and sharing

P

• Problem domain
  • The area of analysis that encompasses every activity affecting or affected by a problem
• Problem types
  • The various problems that data analysts encounter, including categorizing things, discovering connections, finding patterns, identifying themes, making predictions, and spotting something unusual

Q

• Query language
  • A computer programming language used to communicate with a database

R

• Root cause
  • The reason why a problem occurs

S

• Stakeholders
  • People who invest time and resources into a project and are interested in its outcome
• Scope of work (SOW)
  • An agreed-upon outline of the tasks to be performed during a project
• SMART methodology
  • A tool for determining a question’s effectiveness based on whether it is specific, measurable, action-oriented, relevant, and time-bound

T

• Technical mindset
  • The ability to break things down into smaller steps or pieces and work with them in an orderly and logical way

U

• Understanding context
  • The analytical skill that has to do with how you group things into categories

miscellaneous

• 人の分析
  • 協力者を募ること
• 主題の専門家
  • ドメイン知識ホルダーのこと(ビジネス担当者のイメージ)
• 重要な6つのこと
  • ask -> 何をしたいのかヒアリングし、プロジェクトのゴールを明らかにする
  • prepare -> データの生成、収集、保存、およびデータ管理
  • process -> データクリーニング/データ整合性
  • analyze -> 発見とドキュメント化を行う(データの探索、視覚化、分析)
  • share -> 結果をコミュニケーションする
  • act -> アクションの実装を行う
• 本能のバイアス
  • 本能に基づいて何かを決めるとき（そうせざる得ないとき）間違いを導くことがある
  • 本能を抑制する手段として、ドメイン知識を得ることで解決することができる
  • data + business knowledge -> solve
  • 正しい本能をgut instinctと呼ぶ

データ分析のプロセス

• Data life cycle
  • Plan
  • Capture
  • Manage
  • Analyze
  • Archive
  • Destroy
• Data Analysis Process
  • Ask
  • Prepare
  • Process
  • Analyze
  • Share
  • Act

take action with data

• Ask
  • Define the problem you’re trying to solve
  • Make sure you fully understand the stakeholder’s expectations
  • Focus on the actual problem and avoid any distractions
  • Collaborate with stakeholders and keep an open line of communication
  • Take a step back and see the whole situation in context
• Prepare
  • What metrics to measure
  • Locate data in your database
  • Create security measures to protect that data
• Process
  • Using spreadsheet functions to find incorrectly entered data
  • Using SQL functions to check for extra spaces
  • Removing repeated entries
  • Determining if your data is biased
• Analyze
  • Perform calculations
  • Combine data from multiple sources
  • Create tables with your results
• Share
  • Make better decisions
  • Make more informed decisions
  • Lead to stronger outcomes
  • Successfully communicate your findings
• Act
  • Recognizing the current problem or situation
  • Organizing available information
  • Revealing gaps and opportunities
  • Identifying your options

Six problem types

SMART questions

魅力のあるダッシュボード

データの大小