01Gs. Norjamaliah Binti Hussin-Empowering Big Data Analytic Driving Digital Innovation through MD Analytic and SuperMap.pdf

《01Gs. Norjamaliah Binti Hussin-Empowering Big Data Analytic Driving Digital Innovation through MD Analytic and SuperMap.pdf》由会员分享，可在线阅读，更多相关《01Gs. Norjamaliah Binti Hussin-Empowering Big Data Analytic Driving Digital Innovation through MD Analytic and SuperMap.pdf（27页珍藏版）》请在三个皮匠报告上搜索。

1、P1Transform your organizations data into actionable insights with our powerful analytics solutionsEmpowering Big Data Analytics:Driving Digital Innovation through MD Analytic and SuperMapP2Agenda2.WHAT IS BIG WHAT IS BIG DATA DATA ANALYTICS?ANALYTICS?3.5.4 V OF BIG DATA 4 V OF BIG DATA ANALYTICS ANA

2、LYTICS CHARACTERISTICSCHARACTERISTICS TYPES OF TYPES OF ANALYTICSANALYTICS4.6.KEY KEY FEATURESFEATURES1.COMPANY COMPANY PROFILEPROFILE7.INTRODUCTION INTRODUCTION TO MD TO MD ANALYTICSANALYTICSMD ANALYTICS MD ANALYTICS TOP BIG USE TOP BIG USE CASE CASE 8.USE CASE 1USE CASE 19.DEMO DEMO VIDEOVIDEOP3Co

3、mpany ProfileP4P5P6P7P8What is Big Data Analytics?P9The Global Data ChallengeDespite the rise of big data,most organizations still struggle to turn raw data into actionable insights.More data is not more insight unless we can analyze it effectively.Lets explore how MD Analytic,in collaboration with

4、SuperMap,addresses this challenge.P10Collectollect DataataFrom diverse sourcesAnalyzenalyze PatternsatternsUsing advanced techniquesUncoverncover InsightsnsightsFor actionable decisionsBig Data Analytics is the use of advanced techniques to examine large and diverse datasets for uncovering hidden pa

5、tterns,correlations,and actionable insights.Sourcesources:IoT,sensors,apps,social media,financial data,and more.“What is BigData Analytics?”P11Challenges in Big Data ImplementationLack of ResourcesOrganization struggle to find and retain data scientists and analysts with the necessary expertise.Disc

6、onnected data sourcesData silos prevent comprehensive analysis and create inconsistent views across departments.No unified platformMultiple tools and systems create complexity and hinder efficient data processing.Poor onboarding and adoptionLack of skilled resourcesComplex interfaces and steep learn