投稿時間:2023-06-13 08:31:45 RSSフィード2023-06-13 08:00 分まとめ(40件)

カテゴリー等	サイト名等	記事タイトル・トレンドワード等	リンクURL	頻出ワード・要約等/検索ボリューム	登録日
IT	気になる、記になる…	Apple、M2 Max/M2 Ultraチップを搭載した新型｢Mac Studio｣を本日発売	https://taisy0.com/2023/06/13/172886.html	apple	2023-06-12 23:00:00
IT	気になる、記になる…	Apple、M2 Ultraチップを搭載した新型｢Mac Pro｣を本日発売	https://taisy0.com/2023/06/13/172884.html	apple	2023-06-12 23:00:00
IT	気になる、記になる…	Apple、｢MacBook Air 15インチ｣を本日発売	https://taisy0.com/2023/06/13/172882.html	apple	2023-06-12 23:00:00
IT	気になる、記になる…	Apple、｢iOS 16.5.1｣をまもなくリリースか	https://taisy0.com/2023/06/13/172943.html	apple	2023-06-12 22:59:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] トヨタ、EV用「全固体電池」を2027年実用化　生成AIの車載も視野	https://www.itmedia.co.jp/business/articles/2306/13/news071.html	itmedia	2023-06-13 07:29:00
IT	ITmedia 総合記事一覧	[ITmedia News] MicrosoftのActivision Blizzard買収、FTCが連邦地裁に仮差止命令申請	https://www.itmedia.co.jp/news/articles/2306/13/news070.html	activision	2023-06-13 07:04:00
AWS	AWS Marketplace	How to update your single-AMI products in AWS Marketplace using self-service	https://aws.amazon.com/blogs/awsmarketplace/update-single-ami-products-aws-marketplace-using-self-service/	How to update your single AMI products in AWS Marketplace using self serviceAWS Marketplace now enables sellers independent software vendors ISVs and consulting partners CPs the ability to update your single AMI products using self service In this blog post I show how to use the self service feature to update the different features of single AMI products listed in AWS Marketplace	2023-06-12 22:20:38
AWS	AWS	AWS SAM Explainer Video | Amazon Web Services	https://www.youtube.com/watch?v=E7QAhLHOUu8	AWS SAM Explainer Video Amazon Web ServicesThe AWS Serverless Application Model or SAM is an open source Infrastructure as Code IaC tool that simplifies and improves the developer experience of building and running serverless applications on AWS For more information visit Learn how you can use SAM to express APIs functions databases and event source mappings to define the application you want in a few simple lines Then learn how you can use SAM CLI to build test debug and deploy applications defined by your SAM templates Subscribe More AWS videos More AWS events videos Do you have technical AWS questions Ask the community of experts on AWS re Post ABOUT AWSAmazon Web Services AWS is the world s most comprehensive and broadly adopted cloud platform offering over fully featured services from data centers globally Millions of customers ーincluding the fastest growing startups largest enterprises and leading government agencies ーare using AWS to lower costs become more agile and innovate faster SAM serverless lambda IaC AWS AmazonWebServices CloudComputing	2023-06-12 22:39:30
海外TECH	DEV Community	Data roles in data teams and your skill set. Using math	https://dev.to/pedrohgoncalves/data-roles-in-data-teams-and-your-skill-set-using-math-1332	Data roles in data teams and your skill set Using mathData roles and skill setWith GPT some data positions have become quite famous especially data scientists but there are others that deserve the same attention In this article I will show what they are what are the main activities they develop and the set of skills they exercise It is open for discussion I ll try to keep it updated as I change my opinions which I certainly will About the method I chose I listed the most used abilities in the data area and compressed them until they were in common use between at least positions It is important to point out that I did not focus only on hard skills and that soft skills are just as important I gave grades from to based on my experience according to the use and the necessary level of knowledge for that skill Skill explanationsApplied math Applied mathematics is the area of mathematics that looks for ways to solve problems in companies especially in areas of finance expansion logistics and marketing it is widely used mandatory skill for people who deal with data in data oriented companies The grades increase as the position needs to be closer to business related indicators such as revenue operating costs CHURN retention etc Advanced math Firstly with advanced mathematics focused on data I mean the use of some areas such as calculus probability advanced statistics linear regression among many other areas it is distinguished from applied mathematics because unlike it advanced mathematics does not pass by lots of changes in functions due to business rules as opposed to applied math which is basically modeled by business rules SQLAlthough it is quite obvious that functions around data must have knowledge in SQL this knowledge does not have the same levels in different positions SQL subsets are responsible for this great differentiation of levels since many of the positions do not necessarily need to know DCL DDL DML commands The levels serve precisely to separate the subsets following this line of reasoning I created a straight line of wisdom DQL gt DTL gt DQL ADVANCED gt DML gt DDL gt DCLProgrammingProgramming is very present in the data areas whether in languages such as python scala pl sql for creating routines and pipelines or M DAX for manipulating data in specific software The increase in grades in the various areas has to do with how much code the job requires you to write thoughtfullyalong with the languages and the framework that you will use in your day to day BusinessWith business I took the liberty to add some soft skills like communication and general market knowledge in the imaginary equation Knowledge about the business in which the company you provide your services is basic for any position be it development commercial marketing etc but how much business do you need to understand to be able to act minimally in the positions I didn t use any mathematical formula or quantitative driver to define this just my experience and knowledge in BI functions InfraThe infra skill refers to knowledge of deployment monitoring pipe lines identifying bottlenecks and needs it is basically focused on software and frameworks such as docker terraform cloud architecture metadata among others it is very similar to the set of devops practices Particularly it is a skill or No low code softwaresSome positions require you to use some no low code software for developing dashboards pipeline documentation deployment etc The different levels are related to how much knowledge you should have about these tools and how much you will use them in your day to day life PonderationThe weight of the skill is greater in relation to the difficulty in learning its basics Weighting is an attempt to say how complex a position is in relation to the activities it performs and which are listed in the method the account is Applied math Advanced math SQL Programming Business Infra No low code The weights of the weights were based on experience learning certain things related to skills and on informal surveys of some developers and data professionals The higher the grade the greater the difficulty DON T take it as true Positions Data analytics The data analyst works in the opposite direction of the data scientist focusing on talking about how and why things happened rather than making hypotheses about what might happen This position usually works by participating more actively in meetings and creating dashboards so that the company s activity points can consume or that it can help in decision making either making the analyzes more accurate or delivering the data as chewed up as possible using a lot of visualization like tools It gives good points to no low code software because knowledge of tools like power bi tableau excel pentaho etc they are in high demand for vacancies and are allocated good working hours Applied mathematics and business follow the same path generating insights with data and extracting information that generates value for the business requires knowledge about them For SQL and advanced math you don t need in depth knowledge you often won t need to elaborate complex queries or do a linear regression calculation Data analytics skills set points Data engineer Quoting the good article by Maxime Beauchemin former data engineer at Facebook now Meta data engineers are much closer to their older brother Software Engineer than to their younger brother Data Scientist that s why instead of creating machine learning models deep learning data visualization or anything related first of all a data engineer he creates the necessary tooling to abstract as much as possible from technical activities related to modeling mining and manipulation of data creating pipelines data lakes and data warehouses Data engineers are responsible for database modeling mining and data manipulation this explains why I gave SQL a in the skill along with in programming like routines in Python with Airflow or creating pipelines in Scala due to the large amount of data In the day to day of a data engineer at IDEAL reports or visualizations are not created for use on commercial fronts nor machine learning or deep learning models which is why the low grade in applied and advanced mathematics The high score on infra is due to the fact that data engineers are very responsible for deployment environments therefore knowledge in docker terraform cloud etc they are in great demand in vacancies and occupy good hours of work Data engineers skills set points Data ops Yes I know that data ops is not a person occupying a vacancy but a culture equal to devops but there was a materialization of the culture in which a person was leading the fronts for data ops as happened in devops in fact other positions were born derivatives of dataops like ml ops which is basically data ops focused only on machine learning so I think it s fair to materialize the culture in this text A dataops mainly takes care of monitoring pipelines studying business needs new possibilities and improvements He ensures data security reliability and quality but he also participates in budget meetings and architecture definitions abstracting that responsibility from data engineers so obviously he gives full marks in infrastructure and also in business The reason for the high score in programming is due to the configuration of environments and knowledge in the most diverse software aimed at deployment and the software life cycle Even though it seems counterintuitive to ensure data quality and I didn t give high marks in SQL I don t think advanced knowledge of SQL is needed to do this The grade in Advanced Mathematics is explanatory and the reasonable grade in Applied Mathematics is due to the participation in financial issues that are related to the operational costs of keeping the applications available and with a satisfactory level of use Data ops skills set points Data scientist Data science is probably the most famous position on data in recent times Her reputation is equally equivalent to the difficulty of becoming one because the activities that a data scientist performs are extremely complex even with the tools abstracting most of the things that are more complex such as complex calculations collecting and cleaning data The high marks in both math skills is self explanatory you need to know both very well to develop artificial intelligence models that make sense for your business this goes directly with business knowledge which is also needed but not at a very high level In the ideal world the data scientist is abstracted from functions that involve infra and even the collection and cleaning of data a minimum knowledge is enough With the popularization of AI several no low code software are emerging that abstract most of the complex tasks in the day to day of a data scientist but knowledge in programming is still necessary mainly in languages ​​such as R and Python and their frameworks which are references in the area and therefore the medium score in programming Data scientist skills set points Some considerations Perhaps you have already heard of some other functions such as ML Engineer BI Specialist or others these functions exist but they are consistent with the business model in which it is mentioned they are usually ramifications of the mentioned aboveRepository with csv and code for images Thank you very much for reading	2023-06-12 22:08:08
金融	金融総合：経済レポート一覧	FX Daily（6月9日）～139円台を中心とした値動き	http://www3.keizaireport.com/report.php/RID/541027/?rss	fxdaily	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	SECと暗号資産交換業者がいよいよ本格対決へ：暗号資産の衰退への一歩か新たな進化のきっかけか：木内登英のGlobal Economy ＆ Policy Insight	http://www3.keizaireport.com/report.php/RID/541035/?rss	lobaleconomypolicyinsight	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	年金額の目減りは2024年度以降も続くが2026年度には繰越の可能性～2023年度の年金額と2024年度以降の見通し(4)：基礎研レポート	http://www3.keizaireport.com/report.php/RID/541038/?rss	見通し	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	観光業界におけるクラウドファンディング活用マニュアル ～持続可能な観光に資するデジタル技術を活用した新たな資金調達手法の活用に向けて	http://www3.keizaireport.com/report.php/RID/541045/?rss	資金調達	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	FDICによるシグネチャーバンク（SBNY）の監督に関する報告書の概要	http://www3.keizaireport.com/report.php/RID/541051/?rss	日本証券経済研究所	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	プライベート市場の拡大と「ゲートキーパー」：証研レポート	http://www3.keizaireport.com/report.php/RID/541052/?rss	日本証券経済研究所	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	ナショナル・ストック・エクスチェンジ・オブ・インディア～世界最大のデリバティブ取引所：証研レポート	http://www3.keizaireport.com/report.php/RID/541053/?rss	世界最大	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	ＳＥＣによる最良執行ルール提案：証研レポート	http://www3.keizaireport.com/report.php/RID/541054/?rss	日本証券経済研究所	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	米国株価情報配信政策をめぐるＳＥＣと取引所の争い—ＳＥＣによるＳＩＰの改革提案と敗訴：証研レポート	http://www3.keizaireport.com/report.php/RID/541055/?rss	日本証券経済研究所	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	アジア主要通貨・株価の動き（6月9日まで）	http://www3.keizaireport.com/report.php/RID/541058/?rss	国際金融情報センター	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	トルコリラは新たな財務相と中銀総裁の下で輝きを取り戻せるか～大幅利上げに動く可能性も、その後に人事面で軋轢が生じる懸念、リラ相場の行方は極めて不透明：Asia Trends	http://www3.keizaireport.com/report.php/RID/541075/?rss	asiatrends	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	投資先に困る？投信市場～2023年5月の投信動向：研究員の眼	http://www3.keizaireport.com/report.php/RID/541077/?rss	研究所	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	金融セクターにおけるESGデータ市場の進化の様相と課題	http://www3.keizaireport.com/report.php/RID/541080/?rss	eyjapan	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	水素とネットゼロ～どの役割が現実的でどの役割が非現実的か？	http://www3.keizaireport.com/report.php/RID/541085/?rss	発表	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	株式 米国株 S＆P500指数の5つのポイント（2023-6）	http://www3.keizaireport.com/report.php/RID/541101/?rss	米国株	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	ウィークリーレポート 2023年6月12日号～米国株式は上昇。	http://www3.keizaireport.com/report.php/RID/541102/?rss	三井住友トラスト	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	投資のヒント「豪州のサプライズ利上げと1-3月期GDPを読み解く」	http://www3.keizaireport.com/report.php/RID/541103/?rss	三井住友トラスト	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	日米欧・中銀WEEKの注目点 / 欧州通貨：来月以降の利上げが焦点 / トルコリラ：新財務相＆新中銀総裁でリラに反発の目はあるか：Weekly FX Market Focus	http://www3.keizaireport.com/report.php/RID/541104/?rss	weeklyfxmarketfocus	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	投資環境ウィークリー 2023年6月12日号【日本、米国、欧州、オーストラリア】日米欧の金融政策決定会合控え思惑が交錯、豪・加では予想外の利上げも	http://www3.keizaireport.com/report.php/RID/541105/?rss	三菱ufj	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	グローバルリート市場レポート 2023年6月号～2023年5月のグローバルリート市場（除く日本）(配当込み)（Ｓ＆Ｐ指数ベース）(前月末比)は3.4％下落。	http://www3.keizaireport.com/report.php/RID/541106/?rss	配当	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	【注目検索キーワード】ネイチャーポジティブ	http://search.keizaireport.com/search.php/-/keyword=ネイチャーポジティブ/?rss	検索キーワード	2023-06-13 00:00:00
金融	金融総合：経済レポート一覧	【お薦め書籍】1300万件のクチコミでわかった超優良企業	https://www.amazon.co.jp/exec/obidos/ASIN/4492534628/keizaireport-22/	転職	2023-06-13 00:00:00
ニュース	BBC News - Home	Kylian Mbappe: Paris St-Germain are prepared to sell France forward	https://www.bbc.co.uk/sport/football/65882905?at_medium=RSS&at_campaign=KARANGA	Kylian Mbappe Paris St Germain are prepared to sell France forwardParis St Germain are prepared to sell Kylian Mbappe this summer rather than risk losing him for free next summer after he told the French club he will not renew his contract	2023-06-12 22:12:18
ニュース	BBC News - Home	Trump arrives in Florida ahead of court appearance	https://www.bbc.co.uk/news/world-us-canada-65883615?at_medium=RSS&at_campaign=KARANGA	appearancethe	2023-06-12 22:55:24
ニュース	BBC News - Home	Le Mans 24 Hours: Danger, beauty & hydrocarbon - why the race is more important than you realise	https://www.bbc.co.uk/sport/motorsport/65874444?at_medium=RSS&at_campaign=KARANGA	Le Mans Hours Danger beauty amp hydrocarbon why the race is more important than you realiseThe th anniversary of the first edition of the Le Mans Hour race tapped into the event s glorious past What it might mean for the next years of motoring is just as profound	2023-06-12 22:49:40
ニュース	BBC News - Home	US Open: Matt Fitzpatrick and Cameron Smith on PGA Tour-PIF merger plans	https://www.bbc.co.uk/sport/golf/65886176?at_medium=RSS&at_campaign=KARANGA	US Open Matt Fitzpatrick and Cameron Smith on PGA Tour PIF merger plansThe proposed merger of the PGA Tour and Saudi Arabian Public Investment Fund is confusing to players says US Open champion Matt Fitzpatrick while Cameron Smith thought it was a joke	2023-06-12 22:47:17
ビジネス	ダイヤモンド・オンライン - 新着記事	ネトフリ、初のスポーツ中継で交渉中　有名人ゴルフコンペ - WSJ発	https://diamond.jp/articles/-/324385	有名人	2023-06-13 07:28:00
ビジネス	東洋経済オンライン	世界的ブーム！サウナ｢3つの絶大効果｣はこれだ ｢"デジタル汚染"の時代｣に求められる納得の訳 | 健康 | 東洋経済オンライン	https://toyokeizai.net/articles/-/674467?utm_source=rss&utm_medium=http&utm_campaign=link_back	東洋経済オンライン	2023-06-13 07:30:00
IT	週刊アスキー	ファミマ「1個買うと、1個もらえる」が今週も！ 「クラフトボス」「パイの実」などもらえる	https://weekly.ascii.jp/elem/000/004/140/4140633/	対象商品	2023-06-13 07:30:00
ニュース	THE BRIDGE	WordPress、コンテンツライティングを強化するジェネレーティブAIアシスタントをローンチ——日本語にも対応	https://thebridge.jp/2023/06/wordpress-launches-generative-ai-assistant-to-enhance-content-writing	WordPress、コンテンツライティングを強化するジェネレーティブAIアシスタントをローンチー日本語にも対応WordPressは、ユーザのブログ記事の作成と編集を支援する、独自のAIを搭載したライティングアシスタントを発表した。	2023-06-12 22:15:03
ニュース	THE BRIDGE	セールスフォース、「Marketing GPT」と「Commerce GPT」を発表——各種製品へのジェネレーティブAI導入強化へ	https://thebridge.jp/2023/06/salesforce-doubles-down-on-generative-ai-with-marketing-gpt-and-commerce-gpt	セールスフォース、「MarketingGPT」と「CommerceGPT」を発表ー各種製品へのジェネレーティブAI導入強化へCRM大手のSalesforceは日、つの新しいジェネレーティブAI製品をデビューさせた。	2023-06-12 22:00:41