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  1. Data

  2. ​Smartphone

  3. ​AI

  4. ​Renewable Energy

  5. ​GAFA

  6. ​EV

  7. ​GPS

  8. ​SNS

  9. ​YouTube


⭐︎ Basic                 読みやすい
⭐︎⭐︎ Intermediate  読み応えがある

Technology

A smartphone has many functions, including music, video, cameras, and gaming, along with calls and text messaging. The major maker of smartphone are Apple, Samsung, Sony, etc. These companies released models featuring touchscreen in the 2000s. 

 

Apple is ranked as the world's most valuable brand. As many as 1.65 billion Apple products are in use worldwide. Following the iPhone debut in the late 2000s, smartphones have large screens. Smartphone users can download or buy additional applications 

SNS helps people to communicate with other people. SNS is also called social networking site or social media. Users can post their digital photos, movies, and messages online. The popular SNS are Facebook and Twitter.

 

Facebook users can create a profile about themselves. Facebook claimed 2.8 billion monthly active users. Facebook was the most downloaded mobile application in 2010s.

 

Twitter users post and communicate with messages known as "tweets." Tweets were restricted to 140 characters, but the limit was doubled to 280 characters in November 2017.

 

As of 2021, Amazon focuses on e-commerce, cloud computing, and artificial intelligence. It started as an online marketplace for books but expanded to sell electronics, video games, fashion, food, toys, and jewelry. 

Let's Listen
00:00 / 01:38

​テクノロジー

スマートフォンは音楽、動画、カメラやゲームなど多機能に加えて、留守電やテキストメッセージなど携帯電話の機能も持っています。アップル、サムスやソニーが大手で2000年代からタッチパネル式のモデルが投入されています。

アップルのブランド力は世界一で、地球上で16億ものアップル製品が使われています。特にiPhoneの登場で薄く大きな画面が一般的になりました。アプリをダウンロードしたい購入したりできます。

SNSはオンライン交流サイトで写真、動画やメッセージをやりとりできます。主なサービスはフェイスブック、ツイッターです。

フェイスブックは個人プロフィールを作成でき。20人以上が毎月利用しています。メッセンジャーを使って直接やりとりでき、2010年代に最もダウンロードされたアプリです。

​Twitterはつぶやく、というその名のとおりメッセージアプリです。リツイート機能があり、140文字まででしたが280文字に2017年に変わりました。

​アマゾンはEコマースやクラウド、ストリーミングやAIに力を入れています。最初はオンラインの本屋さんですが、商品の種類を増やしています。

Data Analytics ⭐︎⭐︎

What is Data Analytics?

Analytics is the extensive use of data, statistical and quantitative analysis, explanatory and predictive models, and fact-based management to drive decisions and actions.

 

Questions that can be answered by data analytics include:

Question 1. Who are the most profitable customers?

Answer 1.: Use database query to retrieve customers and sort customer spending by cumulative amounts

 

Question 2. Is there a difference between profitable customers and average customers?

Answer 2. Hypothesis testing. For example, the value of profitable customers is significantly different from that of an average customer, with a probability of less than 5 percent. 

 

The benefits of being analytical are broad. 

Better understanding of the dynamics of business environment.

Know what is working for the business and what is not.

Leverage from previous experiences to get more insights, faster execution, and derive more business value.

Cut costs and improve efficiency through optimization techniques. Predictive models can anticipate the future and thus enable businesses to make early adjustments.

 

Data Analytics can be applied to Education.

Some universities analyzed the quantitative and qualitative feedback of the students’ evaluation of their professors.

Classes improve by using shortlist keywords that characterize a good professor.

 

Technology utilized in data analytics includes text mining, sentiment analysis, machine learning, data mining, classification, etc. One of the popular methods is the decision tree. The decision tree is like a root node at the top of the tree, to interior nodes, to leaves representing class values.

 

Clustering is also a useful technique in data analytics. In clustering, samples are separated into two or more separate clusters by characteristics such as color, shape, size, etc. However, there are some issues with clustering. It is often difficult to understand what the clusters reveal.

Let's Listen
00:00 / 02:10

​データサイエンス⭐︎⭐︎

データアナリティクスとは?

統計、定量化、予測や仮説分析を用いて意思決定や行動につなげることです。

例えば、利益率やその理由についてもクエリや特徴を分析したりすることで知見が得られることがあります。

データアナリシスの効果は幅広いです。

ビジネス環境のトレンドがわかったり、効いてる効いていないアクションがわかったりします。

過去から学んだり、より良く実行できたり、事業価値を見つめ直したりもできます。

コストカットや効率化はもちろん、将来に向けた改善活動にも活用できます。

データサイエンスは教育へも活用できます。授業評価を分析したり、より良い授業へのフィードバックなどです。

データサイエンスにはテキストマイニングなどたくさんの手法があります。ディシジョンツリーもよく用いられています。

​クラスターリングも用いられている手法の一つです。母集団を2つ以上の分類に色、サイズや形で分けますが、分類が難しかったり考察が難しいこともあります

Data Analytics ⭐︎

What is Data Analytics?

Analytics is to make some model and/or explanation using data. Based on the analysis, we can choose actions to take. 

 

Questions that can be answered by data analytics include:

Question 1. Who are the best customers?

Answer 1. A1: Use a database to look over customers and sort customer spending. 

 

Question 2. Is there a difference between the best customers and average customers?

Answer 2. Testing. For example, the best customers buy our products much more than the average customer.