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Geweldige resultaten van data-analyse tot praktische toepassingen met https://the-zombillions.nl

In de hedendaagse digitale wereld is data-analyse van cruciaal belang geworden voor bedrijven en organisaties van alle groottes. Het vermogen om grote hoeveelheden gegevens te verzamelen, te interpreteren en te gebruiken om weloverwogen beslissingen te nemen, kan een aanzienlijk concurrentievoordeel opleveren. Echter, het proces van data-analyse kan complex en tijdrovend zijn, en vereist vaak gespecialiseerde kennis en tools. Hier komt https://the-zombillions.nl om de hoek kijken, een platform dat zich richt op het vereenvoudigen van data-analyse en het toegankelijk maken voor een breder publiek. Door innovatieve technologieƫn en gebruiksvriendelijke interfaces biedt dit platform waardevolle inzichten en praktische toepassingen die organisaties kunnen helpen hun doelstellingen te bereiken.

De vraag naar data-analisten en data-gedreven besluitvorming blijft grofweg groeien. Bedrijven realiseren zich steeds meer de potentie van hun data, maar kampen vaak met een tekort aan interne expertise. Dit is waar oplossingen zoals die aangeboden door https://the-zombillions.nl een significante rol spelen. Ze bieden niet alleen de tools om data te analyseren, maar ook de ondersteuning en expertise om de resultaten effectief te interpreteren en te implementeren. Van het identificeren van trends en patronen tot het voorspellen van toekomstige resultaten, data-analyse stelt organisaties in staat om proactief te handelen en zich aan te passen aan veranderende marktomstandigheden. De focus ligt op het omzetten van ruwe data in bruikbare informatie die de bedrijfsprestaties verbetert en de klanttevredenheid vergroot.

Het Belang van Geavanceerde Data-Analyse Technieken

Geavanceerde data-analyse technieken gaan verder dan traditionele methoden zoals statistische analyse en rapportage. Ze omvatten het gebruik van machine learning, kunstmatige intelligentie en predictive modeling om complexe datasets te onderzoeken en verborgen inzichten te onthullen. Deze technieken stellen organisaties in staat om patronen te identificeren die met het blote oog niet zichtbaar zijn, en om nauwkeurige voorspellingen te doen over toekomstige trends en ontwikkelingen. Een belangrijk aspect van geavanceerde data-analyse is het vermogen om real-time data te verwerken en te analyseren, waardoor bedrijven direct kunnen reageren op veranderende omstandigheden. Denk hierbij aan het optimaliseren van marketingcampagnes, het verbeteren van de supply chain efficiƫntie en het detecteren van frauduleuze activiteiten.

De Rol van Machine Learning in Data-Analyse

Machine learning speelt een cruciale rol in moderne data-analyse. Door algoritmen te trainen op historische data, kunnen deze systemen automatisch leren en patronen herkennen zonder expliciete programmering. Dit maakt het mogelijk om grote datasets efficiƫnt te analyseren en voorspellingen te doen met een hoge mate van nauwkeurigheid. Machine learning wordt veelvuldig ingezet voor taken zoals klantsegmentatie, fraudedetectie, aanbevelingssystemen en voorspellend onderhoud. Het is essentieel dat de data die gebruikt wordt voor machine learning van hoge kwaliteit is en representatief is voor de populatie die men wil analyseren, anders kunnen de resultaten vertekend zijn. De toepassing van machine learning vereist vaak specialistische kennis en expertise, maar platforms zoals https://the-zombillions.nl maken deze technologie toegankelijker voor een breder publiek.

TechniekBeschrijvingApplicatie
Regressieanalyse Voorspellen van een continue variabele op basis van andere variabelen. Verkoopvoorspellingen, prijselasticiteit.
Classificatie Indelen van data in verschillende categorieƫn. Spamdetectie, klantsegmentatie.
Clustering Groeperen van data op basis van overeenkomsten. Marktonderzoek, anomaliedetectie.
Beslissingsbomen Visuele weergave van beslissingsregels. Kredietrisicobeoordeling, diagnose.

De inzet van deze technieken helpt bedrijven om betere beslissingen te nemen, risico's te minimaliseren en kansen te benutten. Data-analyse is dan ook een onmisbare component van een succesvolle bedrijfsstrategie.

Data Visualisatie: Inzichten Communiceren

Data visualisatie is het proces van het omzetten van data in grafische representaties, zoals grafieken, diagrammen en kaarten. Effectieve data visualisatie maakt het mogelijk om complexe informatie op een heldere en begrijpelijke manier te presenteren, waardoor besluitvormers snel en gemakkelijk belangrijke trends en patronen kunnen identificeren. Het is belangrijk om de juiste visualisatiemethode te kiezen op basis van het type data en de boodschap die men wil overbrengen. Een staafdiagram is bijvoorbeeld geschikt voor het vergelijken van verschillende categorieƫn, terwijl een lijndiagram ideaal is voor het weergeven van trends over tijd. Effectieve data visualisatie gaat verder dan alleen het creƫren van aantrekkelijke grafieken; het vereist ook een zorgvuldige selectie van kleuren, lettertypen en lay-out om de boodschap helder en overtuigend te communiceren.

Dashboard Design voor Real-time Monitoring

Dashboards zijn een krachtig hulpmiddel voor real-time monitoring van belangrijke prestatie-indicatoren (KPI's). Een goed ontworpen dashboard biedt een overzicht van de belangrijkste data in ƩƩn oogopslag, waardoor besluitvormers snel kunnen reageren op veranderingen en problemen. Het is belangrijk om de KPI's te selecteren die het meest relevant zijn voor de bedrijfsdoelstellingen en om de data op een duidelijke en overzichtelijke manier te presenteren. Dashboards kunnen worden aangepast aan de behoeften van verschillende gebruikers, zodat elk individu de informatie kan zien die voor hem of haar belangrijk is. Platforms zoals https://the-zombillions.nl bieden vaak tools voor het eenvoudig creƫren van dashboards en het integreren van data uit verschillende bronnen.

  • Duidelijke en overzichtelijke lay-out
  • Selectie van relevante KPI's
  • Real-time data-updates
  • Aanpasbare dashboards voor verschillende gebruikers
  • Interactieve elementen voor diepgaande analyse

Door data op een visueel aantrekkelijke en begrijpelijke manier te presenteren, kunnen organisaties hun besluitvormingsprocessen verbeteren en hun prestaties optimaliseren.

Data Governance en Privacy

Data governance en privacy zijn van cruciaal belang in de huidige digitale omgeving. Organisaties moeten ervoor zorgen dat hun data veilig wordt opgeslagen, correct wordt beheerd en in overeenstemming is met de geldende wet- en regelgeving, zoals de Algemene Verordening Gegevensbescherming (AVG). Dit omvat het implementeren van strikte toegangscontroles, het versleutelen van gevoelige data en het regelmatig uitvoeren van audits om de beveiliging te waarborgen. Een effectief data governance beleid omvat ook procedures voor data kwaliteit, data integriteit en data retentie. Het is belangrijk om medewerkers te trainen over data privacy en beveiliging, en om een cultuur van verantwoordelijkheid en bewustzijn te creƫren.

Compliance met de AVG

De AVG stelt strenge eisen aan de verwerking van persoonsgegevens. Organisaties moeten een rechtmatige basis hebben voor het verzamelen en gebruiken van persoonsgegevens, en ze moeten transparant zijn over hoe deze data wordt verwerkt. Individuen hebben het recht om toegang te vragen tot hun persoonsgegevens, deze te corrigeren of te laten verwijderen, en bezwaar te maken tegen de verwerking van hun data. Het niet naleven van de AVG kan leiden tot hoge boetes en reputatieschade. Platforms zoals https://the-zombillions.nl besteden veel aandacht aan data privacy en beveiliging en bieden tools en functies om te helpen bij het voldoen aan de AVG-vereisten.

  1. Implementeer sterke toegangscontroles
  2. Versleutel gevoelige data
  3. Voer regelmatig audits uit
  4. Train medewerkers over data privacy
  5. Zorg voor transparantie over dataverwerking

Het waarborgen van data governance en privacy is essentieel voor het opbouwen van vertrouwen bij klanten en partners, en voor het voldoen aan de wettelijke verplichtingen.

De Toekomst van Data-Analyse

De toekomst van data-analyse wordt gekenmerkt door een aantal belangrijke trends, waaronder de toename van het gebruik van kunstmatige intelligentie en machine learning, de groei van cloud-based data-oplossingen en de verschuiving naar real-time data-analyse. Kunstmatige intelligentie en machine learning zullen steeds vaker worden ingezet om complexe datasets te analyseren, voorspellingen te doen en processen te automatiseren. Cloud-based data-oplossingen bieden organisaties de mogelijkheid om hun data veilig en efficiƫnt op te slaan en te verwerken, zonder te hoeven investeren in dure infrastructuur. Real-time data-analyse stelt bedrijven in staat om direct te reageren op veranderende omstandigheden en om hun besluitvormingsprocessen te optimaliseren.

Data-Analyse in de Praktijk: Een Case Study

Stel een retailketen wil de verkoop van een bepaald product verbeteren. Door gebruik te maken van data-analyse kunnen ze inzicht krijgen in het koopgedrag van hun klanten, de effectiviteit van hun marketingcampagnes en de invloed van verschillende factoren op de verkoop. Door data uit verschillende bronnen, zoals verkooptransacties, websitebezoek, social media en klantonderzoeken te combineren, kunnen ze een compleet beeld krijgen van de klantreis. Met behulp van machine learning kunnen ze vervolgens voorspellen welke klanten het meest waarschijnlijk dit product zullen kopen en welke marketingboodschappen het meest effectief zullen zijn. Deze inzichten kunnen ze gebruiken om gerichte marketingcampagnes te creƫren, de voorraad te optimaliseren en de prijsstelling aan te passen. De beschikbaarheid van platformen, zoals https://the-zombillions.nl, maakt het voor bedrijven van elke omvang mogelijk om de kracht van data-analyse te benutten en hun bedrijfsresultaten te verbeteren. Het is belangrijk om te onthouden dat data-analyse geen doel op zich is, maar een middel om betere beslissingen te nemen en de bedrijfsprestaties te optimaliseren.

Het implementeren van data-analyse vereist een strategische aanpak en een commitment van het hele bedrijf. Het is essentieel om de juiste tools en technologieƫn te kiezen, de juiste vaardigheden in huis te halen en een cultuur van data-gedreven besluitvorming te creƫren. Door data-analyse te integreren in alle aspecten van de bedrijfsvoering, kunnen organisaties een duurzaam concurrentievoordeel opbouwen en hun doelstellingen bereiken.

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