Warum präzise Echtzeit-Daten für Geschäftserfolg kritisch sind

Präzise Echtzeit-Daten zu erhalten ist essenziell für Business. Erfordert: Patterns identifizieren via Metadata, diese Information durch Metadata Files gruppieren, Metadata Accuracy durch Metadata Management Framework sicherstellen.

Real-Time Data Accuracy – Data Quality Characteristic für korrekte Values/Formats – Must für profitables, wachsendes Business. Unternehmen brauchen präzise Echtzeit-Daten für Consumer Demand Influxes. 1/3 C-Suite Executives und Financial Professionals: schätzen Real-Time Financial Data immer mehr.

Leider: Viele Orgs kämpfen weiterhin, Business Insights aus Real-Time Data zu ziehen. Companies sammeln Stunden Streaming Data Feeds – brauchen aber nur paar Minuten für gute Entscheidung.

Selbst Entscheiden, wie Volumes amassed Data validieren → Challenges, schnell zu ermitteln, ob ein Dataset mehr Accuracy hat. Wrong Call → Business verliert $14 Mio.

Glücklicherweise: Metadata (Data about Data) verspricht Hilfe für Real-Time Data Accuracy. Artikel startet Reader Journey: Metadata nutzen für Real-Time Data Accuracy.

Metadata zur Validierung Real-Time Data Accuracy nutzen

Kontraintuitiv: Mehr Data generieren, um bestehende Data Accurate zu halten. Aber Metadata hat Superpowers:

• Wenn Accurate: Metadata liefert Context über beschriebene Information → beweist Data Accuracy. Computer Program → Metadata in Schema/Representation Turnen.
• Metadata Definitions enthalten Kombination Technical/Business/Operational Descriptions Datasets. So: Systems/Processes/People nutzen Metadata → Customers/Purchases/Products/Locations etc. charakterisieren.
• Algorithms nutzen Technical Metadata → Flag Another Process/Person für Further Action.
• Metadata wrapt um Massive Chunk Data → macht Data More Findable.

Zwei Experten, Romero und Calders, nutzten Metadata Strengths mit Approach „Information Profiling“. Framework: Metadata anwenden für Schema Formation Profiling, dann Results enclose via Metadata.

Findings Further: Companies nutzen Business Rules → Guide Metadata Formation Schema, Group Data in Packets wrapped by Metadata. Orgs → Efficienter Way Real-Time Data Deal: Algorithms Look For Data Patterns, Retrieve Matching Datasets.

Real-Time Data Accuracy Example Exploring

Wie Metadata für Real-Time Data Accuracy aussieht Real Life? Gordon & Shankaranarayanan, Babson College, geben Insight.

Company A Feed: Hunderte Instant Messages/Stunde. Customer John Doe textet: Will Bike kaufen von Company A. Company A Validate: Messages von John Doe + Er Will Bike Kaufen.

1. Application Erstellt John Doe Profile = Metadata über John Doe. Werte: Phone Number, Mobile Phone Type, Membership Status Company A. John Doe Representation = Good as Data in Company A CRM.

2. Computer Program Takes John Doe Profile → Matches mit Text Streaming in Feed, Business Rules Define What to Look For in Data Stream. Software Sees Data Matching John's Schema Doe → Bundles Together Under Content Metadata File. Content Metadata File Searchable By People → Assured Text Messages From John Doe (If Metadata Quality Met Business Needs).

3. Algorithm Puts Together Purchasing Profile → Likelihood John Doe Purchasing Bike (wie Amazon Product Recommendations). Dann Algorithm Applies Purchasing Profile → Weighs Likelihood John Wants Bike.

Metadata Accuracy Critical Machen

Note: Metadata für Schema/Batch Erstellung hängt Heavy von Metadata Accuracy Ab. Otherwise: Ensuring Real-Time Data Accuracy Impossible.

Example Above: John Doe Changed Phone Number, Metadata Still Old Number → John's Metadata Inaccurate. Likewise: Metadata File mit Real-Time Data Sets muss Correctly Labeled. Wenn Metadata mit John Doe Text Files Wrong Customer Name → Person Not Find John's Text File.

So: Same Reasons/Processes Companies Use Monitor Data/Cleanse → Consistently Deliver High Data Quality → Apply to Metadata. Metadata Used Validating Real-Time Must Be Adequately Accurate → Confidence About Real-Time Data Accuracy.

Metadata Management Framework

Reicht: Automate Metadata Monitoring/Cleansing? No. Enough Metadata Quality Valuable/Accessible Business Depends On Metadata Management Framework.

Org's People, Processes, Technologies = Metadata Management Framework + Business Rules Creating It.

Example: One Department Standardizes Customer Names In One System, Another Department Formats Different In Separate App → Shaky Metadata Management Framework. Which Department Metadata Take?

Developing Metadata Management Framework Für Adequate Real-Time Data Accuracy Requires:

• Metadata Management Assessments: Existing Structures + Impact. Baseline → Figure Out Processes To Change.
• Data Strategy: Plan Using Data Keep Business Going/Growing.
• Data Governance: Program Coordinating Metadata Access/Security → Remain Compliant.
• Collective Data Literacy: Metadata Importance/Value Determining Real-Time Data Accuracy. Plus: Workers Need Know How Define Good Metadata.
• Solid Business Requirements: Attributes/Values Defining What/Who Metadata Describes.

Abschließende Worte

2020: Companies Saw Why Real-Time Data Quality Needed, While Mistrustful Getting Business Insights From This Data. High Data Volumes/Speeds → Significant Obstacles Quickly Assure Each Piece Data Accuracy In Text/Message Stream.

Curating Real-Time Data Using Metadata Schema + Business Rules → More Value Obtain While Saving Company Resources Analyzing Irrelevant Data. Chunking Results + Labeling Data Sets Using Metadata → Finding Accurate Data Faster. But: Using Metadata This Way Requires Accurate Metadata + Adequate Metadata Management Structure → Business Trust In Real-Time Data Accuracy.