209
KEData analytics = turning raw information into clear business action.
ㅤ
Clean the data.
ㅤ
Find the patterns.
ㅤ
Translate the insight.
ㅤ
Support the decision.
ㅤ
That’s the real skill most people overlook.
@kedeishaindata
#Datainmotion
世界中の人々によるDatainmotionに関する件のリール動画を視聴。
ログインせずに匿名で視聴。
トレンドリール
(12)
427
DADon’t just produce average charts. Create data stories. #dataawesome #analytics #datastorytelling #data
@data.awesome
108
THData Analysis is much more than writing queries and building dashboards.
#fyp #data #DataAnalyst #businessintelligence #dataanalysis
@the_dataevangelist
224
KEMost people aren’t stuck because they’re bad at data.
ㅤ
They’re stuck because they’re chasing a polished fantasy of what the job looks like.
ㅤ
Data analytics is still a great, high-paying career.
ㅤ
But the people who succeed understand the real day-to-day — not the Instagram version.
ㅤ
Before you commit to this path, make sure you’re choosing the reality… not the highlight reel.
@kedeishaindata
378
DSThe beauty of data lies in its patterns.
@dswithdennis
140
THMost data analysts are asking the wrong question first.
They open the dashboard and say,
“What does the data say?”
Please pause.
Before you ask what the data says, ask this:
What does success look like?
Data analyst to data analyst, this will change how you work.
If you don’t define success first, you start wandering.
Opening your dataset doesn't automatically give you direction but having a direction gives your dataset meaning.
If success is:
✔️ Increasing retention by 5%
✔️ Reducing churn in month one
✔️ Improving conversion on a specific funnel step
✔️ Shortening time to value
Now your analysis has a foundation and every metric you use has context.
Without this in place, you are just describing reality and not improving it.
When you ask, “What does success look like?” you force the room to decide:
▶ What are we optimizing for?
▶ What trade-offs are we willing to make?
▶ What metric matters most when they conflict?
Every analysis should have a target.
Because once success is defined, the data becomes a tool to get to that target.
Your data must always connect to a decision.
Always remember that data is powerful, but only when it knows where it’s going.
Found this helpful? Save and share it to help other aspiring data analyst who needs it.
I'll see you in the next one.
☛ You're welcome!
.
.
©️ Goodness | The Digitor
I'm a DATA ANALYST and TECH WRITER for TECH BRANDS and I’m on a mission to help newbies like you go from shy, confused, broke and invisible, to confident, skilled, paid and positioned for global opportunities.
You can now book a 2 hours 1:1 virtual clarity call with me here: https://coachli.co/thedigitor/SV-S0XWp
Anyhooo, I have 2 FREEBIES for you and I'm so sure you'll love them. Get them here: https://linktr.ee/thedigitor
@thedigitor_
117
DAData analysts don’t panic… we just sit there refreshing like it’s going to resurrect itself 💻✨
Moral of the story: No data = no decisions = no productivity 😅
If you know, you KNOW.
Comment 💻 if you’ve ever been personally victimized by a down server
& follow for more real life data analyst moments + tips 💡
@data_analytics_simplified
117
THWhy Most Dashboards Are Useless
#fyp #data #businessintelligence #DataAnalyst #dataevangelist
@the_dataevangelist
0
DSData insights drive smarter business decisions.
@dswithdennis
116
IAStop Building Dashboards Like This | Analytics Reality.
The Real Difference Between a Dashboard and a Data Product.
Many analysts focus on building dashboards, but the real challenge in modern analytics is building trust in data.
When teams define metrics differently — like “Active Users” — alignment disappears and decision-making becomes difficult.
The real role of analytics professionals, business analysts, and data analysts is not just creating charts or writing SQL. It’s about defining metrics clearly, preventing KPI drift, and creating a single source of truth.
In this video, I explain the difference between a dashboard and a data product — and why this mindset shift is critical if you want to become a high-impact analyst.
Follow for more insights on business analysis, analytics careers, data strategy, and becoming a top 1% professional.
@iamwasimparwez
#businessanalyst
#dataanalytics
#dataanalyst
#analyticscareer
#powerbi
businessanalysis
datadriven
careergrowth
techcareer
productanalytics
analyticsmindset
corporatelife
top1percent
learnanalytics
datastrategy
business analyst, data analyst, dashboard vs data product, data analytics career, business intelligence, analytics strategy, power bi dashboard, data governance, kpi definition, single source of truth, analytics best practices, modern data stack, data product mindset, business analysis career
@iamwasimparwez
1.1K
DSBoost operational efficiency with data science
@dswithdennis
115
THWhy Small Errors Become Big Problems
#fyp #data #businessintelligence #DataAnalyst #dataevangelist
@the_dataevangelist
✨ #Datainmotion発見ガイド
Instagramには#Datainmotionの下にthousands of件の投稿があり、プラットフォームで最も活気のあるビジュアルエコシステムの1つを作り出しています。
#Datainmotionは現在、Instagram で最も注目を集めているトレンドの1つです。このカテゴリーにはthousands of以上の投稿があり、@dswithdennis, @data.awesome and @kedeishaindataのようなクリエイターがバイラルコンテンツでリードしています。Pictameでこれらの人気動画を匿名で閲覧できます。
#Datainmotionで何がトレンドですか？最も視聴されたReels動画とバイラルコンテンツが上部に掲載されています。
人気カテゴリー
📹 ビデオトレンド: 最新のReelsとバイラル動画を発見
📈 ハッシュタグ戦略: コンテンツのトレンドハッシュタグオプションを探索
🌟 注目のクリエイター: @dswithdennis, @data.awesome, @kedeishaindataなどがコミュニティをリード
#Datainmotionについてのよくある質問
Pictameを使用すれば、Instagramにログインせずに#Datainmotionのすべてのリールと動画を閲覧できます。あなたの視聴活動は完全にプライベートです。ハッシュタグを検索して、トレンドコンテンツをすぐに探索開始できます。
パフォーマンス分析
12リールの分析
💡 トップ投稿は平均524.75回の再生（平均の2.1倍）
週3-5回、活動時間に定期的に投稿
コンテンツ作成のヒントと戦略
🔥 #Datainmotionは高いエンゲージメント可能性を示す - ピーク時に戦略的に投稿
📹 #Datainmotionには高品質な縦型動画（9:16）が最適 - 良い照明とクリアな音声を使用
✍️ ストーリー性のある詳細なキャプションが効果的 - 平均長385文字
✨ 多くの認証済みクリエイターが活動中（42%） - コンテンツスタイルを研究
#Datainmotion に関連する人気検索
🎬動画愛好家向け
Datainmotion ReelsDatainmotion動画を見る
📈戦略探求者向け
Datainmotionトレンドハッシュタグ最高のDatainmotionハッシュタグ
🌟もっと探索
Datainmotionを探索