投稿時間:2021-12-09 16:40:46 RSSフィード2021-12-09 16:00 分まとめ(52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、直営店での｢Today at Apple｣のセッションを12月11日より再開へ	https://taisy0.com/2021/12/09/149563.html	apple	2021-12-09 06:01:48
TECH	Engadget Japanese	BALMUDA Phone の実機を触って即買いした理由｜ベストバイ2021	https://japanese.engadget.com/balmuda-phone-055949839-063004404.html	barumudaphone	2021-12-09 06:30:04
TECH	Engadget Japanese	アップルMRゴーグルに早くも2世代目のウワサ。2024年発売でより軽量、高速、バッテリー改善か	https://japanese.engadget.com/second-generation-apple-mr-headset-launch-2024-060203444.html	高速	2021-12-09 06:02:03
ROBOT	ロボスタ	中国エリア初の『LOVOT』常設コーナー 広島県の「エディオン蔦屋家電」に登場 れもん、もみじがお出迎え	https://robotstart.info/2021/12/09/lovot-chugoku-edion-tsutaya.html	groovex	2021-12-09 06:28:45
ROBOT	ロボスタ	【連載マンガ ロボクン vol.207】AIの不良？	https://robotstart.info/2021/12/09/robokun-207.html	yascorn	2021-12-09 06:00:54
IT	ITmedia 総合記事一覧	[ITmedia エンタープライズ] ブロックチェーン技術でレジリエンスを強化するbotネット　Googleが対策に乗り出し	https://www.itmedia.co.jp/enterprise/articles/2112/09/news036.html	glupteba	2021-12-09 15:22:00
IT	ITmedia 総合記事一覧	[ITmedia ビジネスオンライン] 動画クリエイター200人が選ぶカメラメーカー　3位「DJI」、2位「Canon」、1位は？	https://www.itmedia.co.jp/business/articles/2112/09/news132.html	canon	2021-12-09 15:17:00
IT	ITmedia 総合記事一覧	[ITmedia PC USER] Poly、Teams Roomsに対応した会議室ソリューション「Poly Studioキット」新モデル	https://www.itmedia.co.jp/pcuser/articles/2112/09/news133.html	itmediapcuserpoly	2021-12-09 15:06:00
TECH	Techable（テッカブル）	ITエンジニアのリモートワーク率約9割。リモートワークの有無は転職にも影響してくるのか？	https://techable.jp/archives/168409	paiza	2021-12-09 06:00:32
python	Pythonタグが付けられた新着投稿 - Qiita	[py2rb] getattr	https://qiita.com/superrino130/items/7361cbc8c5e8945144a8	pyrbgetattrはじめに移植やってますgetattrPythonclassadefpgselfprintprintgetattrgetattrapgインスタンスメソッドを呼び出しています。	2021-12-09 15:58:43
js	JavaScriptタグが付けられた新着投稿 - Qiita	【Harmoware-VIS】Mapboxなどの外部マップを非表示又は変更	https://qiita.com/ucl_Harmoware_VIS/items/01fa2699d5c986aa48ae	ltHarmoVisLayersmapStylemapboxstylesmapboxlightvgtmapStyleのデフォルト値は以下です。	2021-12-09 15:17:51
js	JavaScriptタグが付けられた新着投稿 - Qiita	[React] keyboardイベントを追加する	https://qiita.com/EGASHIRAAkihide/items/6c4b86583628d3d6eb29	「スペースキー」を入力したときに、対象のオブジェクトの色をランダムに変更するように設計。	2021-12-09 15:10:52
js	JavaScriptタグが付けられた新着投稿 - Qiita	【Harmoware-VIS】移動体アイコンの詳細な表示コントロール	https://qiita.com/ucl_Harmoware_VIS/items/65101957ac581dce3d51	【HarmowareVIS】移動体アイコンの詳細な表示コントロールHarmowareVISとは移動体アイコンの詳細な表示コントロールHarmowareVISは移動体アイコンの「表示位置」は移動データに定義した点の位置と時間から計算しますが、その他の項目は移動データへの定義そのままなので、例えば点間を移動中にサイズや色や方向、グラフの値などは変化しません。	2021-12-09 15:02:54
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	VBによるログイン機能について	https://teratail.com/questions/373015?rss=all	ログイン機能の詳細としては、IDとパスワードが一致していれば次の画面メニュー画面に移り、それ以外はエラーを表示という仕様です。	2021-12-09 15:46:00
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	C++にて画像検索を行いクリックするプログラム	https://teratail.com/questions/373014?rss=all	Cにて画像検索を行いクリックするプログラムcにてopencvを使いUWSCのような画像認識にて対象画像のあいまい検索を行いクリックするプログラムを作りたいと思っております。	2021-12-09 15:45:54
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	実行のタイミングによって出力値がnanになる	https://teratail.com/questions/373013?rss=all		2021-12-09 15:42:48
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	realsense　bagファイル　gpu使用量について	https://teratail.com/questions/373012?rss=all	realsensebagファイルgpu使用量について前提・実現したいことpythonrealsenseDを使用しています現在、realsenseを使いpythonコードでbagファイルを保存しています。	2021-12-09 15:36:47
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	pythonの並列処理について	https://teratail.com/questions/373011?rss=all	pythonの並列処理について疑問点pythonで並列処理を行いたいが、並列処理を行ってくれるコードの違いが分かりません。	2021-12-09 15:36:29
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	コマンドラインで保存する画像の名前を指定するにはどうしたらいいですか？	https://teratail.com/questions/373010?rss=all	コマンドラインで保存する画像の名前を指定するにはどうしたらいいですか画像をコマンドラインで指定して、呼び出すことはできたのですが、コマンドラインで読み込んだ画像を変化させた後に保存するため画像名の指定のやりかたがわかりません。	2021-12-09 15:35:43
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	nav._openが開いたとき、スクロールを禁止させる	https://teratail.com/questions/373009?rss=all	navopenが開いたとき、スクロールを禁止させる前提・実現したいこと目的nbsp表題の通り、navopenが開いたとき、スクロールを禁止させたい。	2021-12-09 15:30:05
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	NoMethodError を解決させたい	https://teratail.com/questions/373008?rss=all	NoMethodErrorを解決させたいNoMethodErrornbspinnbspCustomersOrdersControllercreateundefinednbspmethodnbspcartitemsaposnbspfornbspltCustomerxcfgtnbspDidnbspyounbspmeannbspcartidsnbspcartitemsnbspnbspcurrentcustomercartitems上記のエラーが発生しております。	2021-12-09 15:20:13
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	TkInter: ドラッグ＆ドロップを達成したく　インターネットでの紹介記事を丸々貼り付けたがエラーになってしまう。	https://teratail.com/questions/373007?rss=all	TkInterドラッグドロップを達成したくインターネットでの紹介記事を丸々貼り付けたがエラーになってしまう。	2021-12-09 15:15:35
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	Swiper.jsでボタンの位置を変更できない	https://teratail.com/questions/373006?rss=all		2021-12-09 15:07:06
Program	[全てのタグ]の新着質問一覧｜teratail（テラテイル）	PWAで実装したWEBアプリをネイティブアプリ化したい	https://teratail.com/questions/373005?rss=all	PWAで実装したWEBアプリをネイティブアプリ化したい前提・実現したいことPWAで実装した運用中のWEBアプリをネイティブアプリ化したいです。	2021-12-09 15:02:06
Ruby	Rubyタグが付けられた新着投稿 - Qiita	[py2rb] getattr	https://qiita.com/superrino130/items/7361cbc8c5e8945144a8	pyrbgetattrはじめに移植やってますgetattrPythonclassadefpgselfprintprintgetattrgetattrapgインスタンスメソッドを呼び出しています。	2021-12-09 15:58:43
技術ブログ	Developers.IO	Pythonでpdfを画像として認識しテキストを抽出を試してみる(pyocr)	https://dev.classmethod.jp/articles/export-text-data-from-image-using-python/	pyocrpdf	2021-12-09 06:54:35
技術ブログ	Developers.IO	EC2（Amazon Linux 2022）にターミナルソフトからSSH接続できない場合の対処方法	https://dev.classmethod.jp/articles/tsnote-ec2-rsa-sha-001/	openssh	2021-12-09 06:18:23
技術ブログ	Developers.IO	Coc.nvimを触ってみようアドベントカレンダー 9日目 – coc-cfn-lint	https://dev.classmethod.jp/articles/cocnvim-adventcalendar-day09/	cloudforma	2021-12-09 06:00:25
技術ブログ	Hatena::Engineering	はてなのエンジニア採用向け会社紹介資料を作りました	https://developer.hatenastaff.com/entry/2021/12/recruiting-pitch	はてなでは現在、全方位的にエンジニアを積極採用中です採用活動の中で、はてなでのエンジニア職に興味を持っていただけた方々とお話ししていると、はてなという会社について知ってもらう機会を十分には作れていなかったと感じることが多くありました。	2021-12-09 15:09:33
海外TECH	DEV Community	The Data Stack Journey: Lessons from Architecting Stacks at Heroku and Mattermost	https://dev.to/rudderstack/the-data-stack-journey-lessons-from-architecting-stacks-at-heroku-and-mattermost-2p4o	The Data Stack Journey Lessons from Architecting Stacks at Heroku and MattermostOur current world is defined by information overload From your watch tracking your health to your washing machine notifying you when your clothes are done and your phone tracking everything our personal lives are constantly emitting streams of data It s no different for businesses Many businesses collect the types of product data mentioned above of course but that s only one kind of data Tracking sales leads marketing journeys and customer experiences is now standard to name just a few forms of business data The amount of data produced by your business is immense if harnessed properly it can also be immensely valuable In fact we argue that companies that can leverage this data at scale are able to understand their businesses better and iterate more quickly This unique competitive advantage helps them ultimately win in the marketplace Importantly your efforts at implementing the tools and processes required to create value from data aren t static As your business grows in size and complexity you iterate to adapt to demands from customers and the market This changes how you create value from data We call this process The Data Stack Journey This post is meant to guide you in making good foundational decisions that will give you short term benefit but reduce or eliminate the all too common growing pains that happen as your business and data grow We will cover company stages the core components of the customer data stack and then dig into Alex s recommendations on which components to use at which stage based on his experience building data stack at companies like Heroku and Mattermost The Data Stack JourneyThe moment your business first provisions a database to store data you ve taken your first step on the Data Stack Journey Understanding where you are on your journey can help you choose the right data tools for your business This toolkit will enable you to leverage your data for its maximum impact Ultimately the Data Stack Journey is the evolution of your data data tools and processes over time as your business and data grow and change By choosing the right tools and technologies at the appropriate steps of your Journey you will be able to maximize the value that you re able to extract from your data while also controlling your spending on tools and resources Perhaps most importantly you can make wise decisions early that pay dividends as you grow helping you avoid migration integration work and the need for re architecting for scale Company StagesLet s start by looking at the stages businesses generally go through as they grow from a small startup to an international enterprise As companies evolve so do their data and data technology needs With each stage of growth comes new challenges and we ll specifically call out targeted advice for each stage First Steps  You have a small number of customers that you maintain high touch relationships with The founders are wearing all the hats and most back office processes are being done manually Seed  Your product has gained traction and you re no longer able to personally message every customer Your business has started to generate revenue and you are quickly iterating the product This is generally where Seed and Series A stage VC companies are Most traditional departments such as Sales Marketing etc are staffed by small teams of people Growth  You ve found product market fit and are aggressively growing your market share You have thousands or even more of customers the number also depends on the business model Annual revenue is now in the millions Your organization is starting to feel growing pains and needs to scale and mature This is around where most Series B and C companies find themselves Mature Your business is considered a big player in its market and is considered one of the de facto choices in your segment Product iteration tends to be more deliberate and calculated Optimizing any business metric by even a handful of percentage points could yield millions of dollars of cost savings or revenue Your Grandma has Heard of Them Your business deals with actual Big Data We re talking FAANG level here where data sizes are in terms of Petabytes You re building some of your own internal tools to deal with the scale of your data because there aren t off the shelf solutions for all of your data needs Data Stack ComponentsNow that we ve established the high level stages of companies as they go through the Data Stack Journey let s take a look at the core components of the data stack The customer data stack is a comprehensive complex system so for this post we ve trimmed the list down the core components at the foundation of the stack that every company needs Data warehouse the center of the stack where all of your data is unified and accessible to teams tools apps etc Data transformation  processing and transformation to ensure your data is usable for downstream functionsData visualization  translates data into a usable interface for humans for all kinds of purposes primarily analyticalEvent stream  user behavior data from your websites and appsETL ELT tabular  table data from your cloud appsReverse ETL  sending data from your warehouse to apps and other destinationsData governance  keeping your data clean amp compliant across the entire stack Data Stack Components by StageThis is where the rubber meets the road for companies deciding which components to use at which stage This analysis comes from Alex s experience building and re building data stacks at various stages at companies like Heroku and Mattermost Data WarehouseFirst Step and Seed You most likely can just query your production database though I would recommend using a read replica follower I would say you can run dbt against your production database but I d be very careful and might just skip dbt altogether until you can get a database for analytics only For a while you should be able to get away with using a Postgres database as your data warehouse Growth and larger Once you get to a certain size you ll most likely be looking for a proper data warehouse The top three players at the moment are Google s BigQuery Amazon Redshift and Snowflake I personally put Snowflake and BigQuery as a and b BigQuery has capabilities for streaming data into your warehouse very quickly e g a handful of seconds to get certain sources of data queryable I find Snowflake to be the easiest to use with a more conventional database permission system Also being able to control the amount of compute power by controlling the size of your Virtual Warehouse makes it easy to run your big beefy jobs in a decent runtime It also has interesting features like Snowpipe for pulling data into the warehouse With both BigQuery and Snowflake you need to keep an eye on costs as you re generally paying for how many compute resources you are consuming Redshift is great but is more like a traditional database system to run The benefit to Redshift is that you re just paying a flat amount regardless of how much you do with it You have to spend more time on database administration tasks however such as optimizing column encodings sort keys and distribution keys Also your compute power isn t separate from your storage So if you just need more storage you have to add more nodes to your cluster even if you don t necessarily want to pay for more compute power Data TransformationThe one and only dbt This the one tool I d recommend for companies of any size It provides a framework for transforming the data as part of your ELT process With dbt you define your raw data sources and build models in SQL like templates and then build models that reference other models Because you ve now defined a hierarchy of models dbt can now build your models appropriately based on the graph of models you ve built Dbt will then automatically generate a docs site that allows you to visualize the lineage graph of your models and raw data sources This can really help with onboarding new analysts and data engineers by giving them an easy way to explore how the data is modeled and its lineage Dbt Cloud is a mo developer user with unlimited view only users You can also run dbt yourself through a tool like Airflow In most cases I d start with dbt Cloud since the operational burden of running Airflow yourself could be more than it s worth especially if you re just using it to run dbt Data VisualizationFor First Step and Seed I d recommend Metabase This provides data visualization that won t break the bank For future scalability and maintainability I d recommend leveraging dbt to build models that can answer most questions with simple SQL queries By putting most of the complexity in your dbt models you ensure that users can t get themselves into trouble by incorrectly writing SQL This also allows you to have more portability if you choose to move to a different visualization platform Pricing for Metabase can be as low as mo if you use their cloud service For Growth and larger I would recommend Looker The only reason I wouldn t recommend it for the smaller company stages is that the cost is much higher than alternatives such as Metabase With Looker you define your data model in LookML which Looker then uses to provide a drag and drop interface for end users that enables them to build their own visualizations without needing to write SQL This lets your analytics team scale by not getting bogged down answering one off questions from end users or having to build every chart or graph that your users need Event StreamThere are really only two choices here Segment and RudderStack They are both affordable in the First Step and Seed Stages but RudderStack scales much better through the Growth Mature and Enterprise phases Segment Segment is a mature product with a heavy lean towards marketing and now revenue operations users While Segment will sync your data to your data warehouse a lot of features are restricted to only use data that is in Segment itself This means it s difficult to unlock the real power of your data Also with MTU based pricing you can be forced into situations where you re trying to determine if implementing new telemetry is worth the cost RudderStack RudderStack doesn t store any data they enable you to build a CDP on your own warehouse and their event stream capabilities are as good or better than Segment Also they offer Cloud Extract ELT and Warehouse Actions reverse ETL meaning you don t have to manage your event stream separately from your other pipelines Lastly because they are open source there s no vendor lock in Data GovernanceThis is closely related to the transformations component we covered above so we don t need to go into a ton of detail Ultimately you need to bake data governance into the stack from the beginning and dbt Looker are the tools for the job First Steps and Seed With dbt you can hide the complexity of transforming raw data into usable models and also ensure that internal users are only looking at data from the vetted dbt models Growth and larger With the combination of dbt and Looker you can maintain good data governance Looker gives you the platform to let you unify the definitions of business metrics so that everyone is playing off the same sheet of music ETL ELT Tabular ETL ELT solutions for getting tabular data from your cloud tools to your warehouse are becoming commoditized and that functionality is now ubiquitous among data stacks There are various options and some up and comers to keep an eye out for Pipelinewise  An open source framework for running Singer io taps and targets It s relatively easy to run yourself and can get you started with ETL Recommended for First Steps and Seed  but you can use it as just an additional tool since it s pretty straightforward to use Stitchdata  A SaaS product that also runs Singer io taps and targets The UX is relatively straightforward though there are some rough edges and you can t use cron style scheduling unless you purchase their enterprise plan The pricing is based purely on the number of rows synced and generally is not very expensive FiveTran  This is the premium product in this space with a polished UX but also comes with a higher cost They also have a pricing plan based on monthly active rows which can make it a little more challenging to calculate Recommended for Growth or larger companies RudderStack Cloud Extract  With Cloud Extract you can pull data out of sources and into your warehouse Because it s integrated with the rest of the RudderStack product it is easier to manage without having tons of different tools you have to log into Airbyte  This is a newcomer to the space and is open source They are looking to move away from Singer io formats and are also looking to integrate better with dbt Keep an eye on this one Reverse ETLEnriching data in your business systems from your data warehouse is becoming increasingly important The key is to ensure that each business system is getting populated with accurate data This also allows for the various teams in your company to work with the technologies they are familiar with without having to jump between a bunch of different systems For instance enriching lead information in your CRM with product usage data can help your sales reps engage with customers better and lead to more conversions Reverse ETL can also be instrumental in helping to automate and make business processes more efficient There are a lot of competitors in this space and the dust hasn t yet settled on which is the premier solution Census  As of this writing Census is one of the more mature products in this space Don t underestimate how much a good UX helps to drive adoption within an organization The default pricing model is per connector without charging extra per volume If your organization syncs a ton of data to one destination this could be the solution for you Hightouch  This product is developing quickly One interesting feature is their Git sync for dbt which gives you configuration as code which will help with scalability and maintainability Their pricing is based on the volume of unique records synced to any number of destinations This could be the solution for you if you re looking to sync a relatively smaller number of records to a lot of different destinations Polytomic  This product is a new entrant into the space and they have a couple of interesting twists One is that they don t write to the data source that they re pulling data from which means you can hook it up to a read only replica without issue Also they can join together data from a variety of sources including Google Sheets and push the combined data to a variety of sources If you re in the early stages of your Data Stack Journey this is definitely worth a look RudderStack Warehouse Actions  With RudderStack s warehouse first architecture it dovetails nicely into using your Warehouse to send data to other sources This feature is still developing but looks promising and keeps you from having Yet Another Tool if you have relatively straightforward reverse ETL needs Only You Can Prevent a Messy StackIt s a great time to be a data engineer architecting a customer data stack The tools available allow you to build from the data layer up with your warehouse as the center giving you ultimately flexibility and scalability Perhaps the best news is that there are tools like dbt and RudderStack that will scale with you from your first steps through becoming an enterprise company drastically simplifying your work on the stack and giving you the ability to focus on your product At the end of the day though tools are only the conduit the best companies make data itself a first class citizen in the organization and invest time upfront in data modeling transformations and governance to ensure that no matter which tools are used data stays clean and usable through every stage of growth Sign up for Free and Start Sending DataTest out our event stream ELT and reverse ETL pipelines Use our HTTP source to send data in less than minutes or install one of our SDKs in your website or app  Get started	2021-12-09 06:35:42
海外TECH	DEV Community	Advent of Code 2021 Python Solution: Day 9	https://dev.to/qviper/advent-of-code-2021-python-solution-day-9-4amm	Advent of Code Python Solution Day First part was not much harder to crack but it still took plenty of time But second part was tricky Part import numpy as npdata data get data day dl len data dt np array int d for dt in data for d in dt dt dt reshape dl nums pos dc len dt dr len dt for r in range len dt for c in range len dt if r if c if dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c elif c dc if dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c else if dt r c lt dt r c and dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c elif r dr if c if dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c elif c dc if dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c else if dt r c lt dt r c and dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c else if c if dt r c lt dt r c and dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c elif c dc if dt r c lt dt r c and dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c else if dt r c lt dt r c and dt r c lt dt r c and dt r c lt dt r c and dt r c lt dt r c nums append dt r c pos append r c nums Part I thought I had to use some sort of Searching algorithm like DFS or BFS but I found a solution on StackOverflow using NumPy from scipy import ndimagelabel num label ndimage label dt lt size np bincount label ravel top sorted size reverse True print np prod top	2021-12-09 06:34:20
海外TECH	DEV Community	Identity Resolution is More Valuable When it’s on Your Warehouse	https://dev.to/rudderstack/identity-resolution-is-more-valuable-when-its-on-your-warehouse-40pe	Identity Resolution is More Valuable When it s on Your WarehouseIdentity resolution lets you combine unique identifiers across your digital touchpoints to identify users in real time With it you can create a unified omnichannel view of your customers By leveraging an identity graph a database that houses these identifiers you can identify and connect details related to different aspects of your customers journeys and stitch them all together in one customer profile RudderStack Builds Your Identity Graph on Your Data Warehouse Other Customer Data Tools Don t While many customer data tools offer identity resolution they build and store these identity graphs in their CDP tool infrastructure To the user building the identity graph is opaque and the data that composes the identity graph is unknown RudderStack doesn t do any of that black box magic though One of RudderStack s most prominent features is its warehouse first architecture RudderStack treats your data warehouse as a first class citizen So you can send all your cross platform data to your warehouse in real time More importantly RudderStack lets you build important data structures like your identity graph in your data warehouse This means you can leverage all the cross platform customer data residing in your warehouse to stitch together comprehensive user profiles using the identity graph How Businesses use Identity ResolutionBefore we jump into the advantages of performing identity resolution on your warehoused customer data let s take a quick look at how companies leverage identity resolution in traditional CDP tools ones that store your identity graph on their infrastructure Cross Device Identity StitchingWhile a user may use one browser on a particular device for all their work related activities they may use another device or browser for their personal tasks User behavior differs between devices browsers and even the time of day Your sites and applications generate data that you can use to derive valuable detailed insights such as what users are more likely to do in their free time what their search history looks like on their tablet and so much more Combining all of this information lets businesses get a complete picture of who the consumer is on more than one device By connecting different unique identifiers across platforms and devices in real time businesses can enable efficient targeting and personalization Real Time Identification of Users in Downstream ToolsBusinesses often collect event data from multiple disparate digital properties and stream that data to downstream tools Identity resolution allows them to link together all the user IDs and the anonymous IDs IDs assigned to a user before they login or if they don t log in across digital properties for a given user This process involves combining a user s device ID offline ID cookie information etc into a single anonymous identifier allowing brands to identify unique users By leveraging the identity graph residing in a data warehouse you can easily identify aggregate and unify customer profiles from various data silos Building and Activating Segmented Audiences Inside the CDPIdentity resolution lets marketers de duplicate unique users and also monitor their entire customer journey across all digital touchpoints It also allows them to build behavior based cohorts depending on the customer s product interaction between user sessions and devices as well as various real time traits You can use these audiences for various downstream activation use cases such as analytics spend optimization targeted marketing personalized messaging cutting edge customer support and delivering unique customer experiences Additional Benefits of Building Your Identity Graph on Your Data WarehouseWhen you build your identity graph on a data warehouse you get all the advantages of traditional identity resolution plus more Easier More Scalable Cross Device Identity StitchingIn modern digital businesses the graph used for cross device identity stitching can be quite large consisting of tens or even hundreds of millions of nodes This number keeps scaling rapidly as you gather more data across different touchpoints In such a scenario storing the identity graph on your data warehouse and not on the CDP infrastructure makes a lot of sense Cloud data warehouses are infinitely scalable and data storage is cheap RudderStack lets you achieve efficient and seamless identity mapping in your data warehouse It does this by storing the graph on the warehouse as a table associating a virtual ID with all the device IDs user or anonymous ID and mapping the association between them It builds the identity graph for all of your event data and updates it continuously as new event data comes into your warehouse Enrichment of Your Identity Graph with Data from Non Event ToolsApart from your customer event data your warehouse also stores data from different non event tools like CRM and customer support platforms email marketing and advertising tools analytics platforms etc An identity graph built on your warehouse can leverage all of this data to stitch together a more comprehensive enriched user profile giving you a more accurate and real time view of your customers An enriched identity graph built on your warehouse also lets you build more effective user cohorts by bringing together information from various event and non event tools all in real time Creating a Unified Customer ProfileIf your data warehouse is the single source of truth for your customers it only makes sense to have your identity graph built on top of this warehoused data With RudderStack you can build a customer identity graph that leverages your enriched warehoused data in real time to provide a single unified view of all your customers It links identifiers such as device IDs cookies email addresses IP addresses etc to a known or anonymous profile while following the required privacy compliant methods You can then leverage this rich identity graph to enable identity resolution and get a complete degree view of your customers You can also use the identity graph to implement other use cases such as lead scoring creating custom cohorts and audience segments for your personalization use cases and much more Sign up for Free and Start Sending DataTest out our event stream ELT and reverse ETL pipelines Use our HTTP source to send data in less than minutes or install one of our SDKs in your website or app  Get started	2021-12-09 06:31:07
海外TECH	DEV Community	Can We Use Medicinal Mushrooms to Treat ADHD?	https://dev.to/aaronprettovopni/can-we-use-medicinal-mushrooms-to-treat-adhd-3l44	Can We Use Medicinal Mushrooms to Treat ADHD According to Aaron Pretto Vopni there is a still consensus on whether medicinal mushrooms are an acceptable and legal form of treatment of ADHD Medicinal mushrooms are when the harvested mushrooms are converted into medicines for treating diseases or illnesses Know with Aaron Pretto Vopni what is ADHD amp medical mushrooms and how medicinal mushrooms can treat people suffering from ADHD	2021-12-09 06:27:03
海外TECH	Engadget	SpaceX launches a NASA telescope that will observe black holes	https://www.engadget.com/space-x-launches-nasa-ixpe-060812924.html?src=rss	SpaceX launches a NASA telescope that will observe black holesA SpaceX Falcon rocket has blasted off with NASA s Imaging X ray Polarimetry Explorer IXPE satellite First announced in the IXPE is the first satellite capable of measuring the polarization of X rays that come from cosmic sources such as black holes and neutron stars nbsp The fridge sized satellite has three telescopes that can track and measure the direction arrival time energy and polarization of light When data from all those telescopes is combined NASA can form images that could give us more insight into how mysterious celestial objects ーthose that emit X ray ーwork For instance they re hoping it can give us a more thorough look at the structure of the Crab Nebula a supernova remnant with a neutron star rapidly spinning in its center By observing black holes the IXPE will help scientists gain more insight and broaden humanity s knowledge on the regions of space we still barely know It could provide clues on why they spin and how they gobble up cosmic materials though it could also lead to new discoveries Martin Weisskopf the mission s principal investigator said during a briefing quot IXPE will help us test and refine our current theories of how the universe works We may even discover more exciting theories about these exotic objects than what we ve hypothesized quot nbsp SpaceX used a Falcon rocket from a previous mission for this launch If all goes well the rocket s first stage will land on the company s drone ship quot Just Read the Instructions quot after ferrying IXPE to space Liftoff pic twitter com vVAbUITLーSpaceX SpaceX December	2021-12-09 06:08:12
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