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big data

big data

What is meant by big data?

"Big Data" refers to large volumes of data that are characterized by their variety, velocity, and volume and are difficult or impossible to process using conventional data processing methods. These data originate from various sources such as sensors, social media, digital transactions, machine logs, and more. Big Data is often used for analysis and extraction of valuable insights, patterns, and trends that assist businesses, organizations, and governments in decision-making and strategy development.

Typical functions of software in the area of big data can include:

  1. Data integration from various sources and formats.
  2. Storage and management of large volumes of data.
  3. Data preprocessing and cleansing to improve data quality.
  4. Scalable processing techniques for large datasets.
  5. Conducting advanced analytics such as machine learning, data mining, and predictive analytics.
  6. Data visualization and creation of meaningful reports.

The function / module big data belongs to:

Big Data

big data
Big Data Analytics
data and text mining
Data Connectors
Data Mapping
Data warehouse
Machine Learning
Multiple data sources

Statistics/Forecast

analyses of covariance
Analysis
Analysis functions
Analysis results
Article hit and rivet lists
Bayesian analysis
Before-and-after comparisons
big data
Bootstrap method
Budget information
Business Impact Analysis
Calendar functions
Capacity evaluations
Cashier hit list
classification and regression trees
Cluster analyses
Clustering
Collaborative Planning
combinatorial problems
comparative statistics
Competitive Analysis
Conjoint analyses
Container accounting
Correlation analyses
Correlation matrix
Correlations
Course statistics
Customer and sales data analysis
Customer evaluations
Customer statistics
Demand forecasting
Downtime Pareto analysis
Econometric and statistical analyses
Employee capacities
Energy price analysis
Error analysis
Excel export
Extrapolation procedure
Financial market statistics
Fluctuation statistics
forecast result
Forecasting
Forecasting
Forecasting and planning
Frequency distributions
Geostatistics
Gibbs sampling
Key figure simulations
KTL evaluation
Linked data management
liquidity analysis
Management evaluations
Mandate analysis
matrix calculus
Mean values
Metropolis algorithm
Network Statistics
Order tracking
Performance analysis
Permutation test
Plausibility checks
Predictions
Predictive analytics
Predictive Modeling
previous year view
Probabilities of occurrence
Probability analysis
Probability distributions
Process visualization
Processing times
Project forecasts
Project ID
Projection comparison
Random generator
Real-time evaluations
Regression analysis
Regressions or equalization calculations
Resume analysis
Risk analysis
Sales comparisons
Sales hit lists
Sales lists
Sales statistics
Sales statistics
Sampling system
Scrap analyses
Seller leaderboard
Sequence analysis
Shopping cart analysis
Signal statistics
Six Sigma
statistical cost planning
Statistics
Sub-process analysis
Subscription shelf life statistics
Survival analysis
Time series analyses
Trend analyses
Trend value analyses
Utilization analysis according to loss classes
Visitor statistics
Weighting functions
What-if analyses

Software solutions with function or module big data:

CellShield
Data Privacy
CoSort
Big Data
Detact®
Production Data Acquisition
elKomBI
Business Intelligence (BI)
gfos.MES
Production Data Acquisition
PRODAT ERP
Production Planning Systems
RowGen
Databases (Applications)
SMARTR.factory
Production Data Acquisition
TARGIT Decision Suite
Business Intelligence (BI)
Textkernel - AI Recruitment Software
Recruitment
Voracity
Big Data