Hadoop Data Governance

Governance with end-to-end Metadata Management

If you have embarked on a hadoop data lake, you are already familiar with how spotty data governance of the lake can be. Governance is not an isolated dictionary, quality, business, process, or tool problem. The data lake must implicitly support automatic metadata capture, tagging, deduplication, profiling, quality, provenance, propensity, and security controls. Our solution provides a WYSIWYG data "manifold" to enforce end-to-end automated metadata controls across the full data lifecycle.

• Hadoop
• Data Governance
• Data Quality
• Deduplication
• Scorecarding
• Data Profiling
• Security Classification

Data Curation & Linking

Automatically collect, curate, and collate raw data through your enterprise data hierarchy

Data is the new oil. But hoarding raw data without transforming it to the enterprise standard is unproductive. Data lake is great to contain data in a single schema-less secure logical warehouse. But if your data lake is not shored up with an enterprise data taxonomy, the datasets are merely "colocated ", not correlated. Data Bloom enables unstructured fuzzy quadratic joins so the data lake can be used to curate raw data and identify latent correlations. Employ Data Bloom to continuously process raw data, mine patterns, link entities, derive business ontologies in a mixed-initiative environment.

• Spark
• Fuzzy Matching
• Entity Linking
• Master Data Management
• Business Data Management
• Taxonomy
• Ontology

Predictive Modeling

Gain foresight into future business performance

Wouldn't it be great to gain prescience for future performance of your markets? While past is a great predictor of the future, not all industries, market segments, products, and geographies are created equal. Separate trends from fluctuations so advance pricing, planning, and promotion strategies can be implemented versus leaving them to guesswork.

• Timeseries
• Regression
• ARIMA
• Econometric models
• Business Planning
• Forecasting
• Predictive Analytics

Sales and Marketing Analytics

Gain and retain customer loyalty

Create and execute successful marketing campaigns for attracting and retaining best customers. Running a healthy business requires loyal customers. Customers will churn unless the right product, service, pricing, and messaging are combined. It is imperative for business to nurture customers into loyal promoters by executing and measuring every campaign's effectiveness in sales and service. With a single enterprise (transactional, operational, customer, finance, clickstream) data lake, it is now easy to execute customer 360° analytics.

• Marketing Analytics
• Sales Analytics
• A-B testing
• Campaign Management
• Business development
• Customer Churn
• Prospect Marketing

Personalized Search Analytics

Deliver superior outcomes for your customers with personalized search

Text search yields good results. But superior results go beyond simple search by combining explicit (stated), implicit (implied), and tacit (observed) intelligence. Each user, context, content, goals are different. Offering same results for diverse personas will indispensably disappoint customers. Demystifying user's complex knowledge goals is very challenging, but user's digital fingerprints can be handy to infer more than is apparent from a simple search query. Tracking-pixel instrumentation is necessary for capturing this intelligence. Mining these homing signals of personalization must be a critical operational component of every search/knowledge enterprise.

• Text Search
• Personalization
• Tracking Pixel
• User Analytics
• Behavioral Analytics
• Collaborative Filtering
• Content Filtering

Deep Learning and Cognitive Applications

Incorporate natural modality into your expert systems

We live in very exciting times where technology can recognize, infer, and react to human stimuli. Watson, in 2011, beat human champions at Jeopardy challenge. That feat was quite astonishing. What it has since done is provoked interest into building "cognitive" intelligence for machines to recognize, reason, and react to realtime conversational queries -- queries like image search, speech recognition, content categorization, text to speech, machine translation, associative reasoning etc -- that was believed an exclusive realm of natural intelligence versus artificial intelligence.

• Deep Learning
• Cognitive Applications
• Speech Recognition
• Image Search
• Tensorflow
• Content Categorization
• Predictive Coding

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