Alternative data has transitioned from a niche concept to one of the most transformational forces in finance and industry. This definitive guide examines all facets of alternative data analytics to assess signals, unlock hidden value and guide strategy.
The Explosive Growth of Alternative Data
Alternative data refers to non-traditional information sourced outside standard financial statements, earnings calls and news reports. From web scrapers to satellite imagery and location data, obscure alternative datasets are capturing global activity down to the minute.
And demand for this data is skyrocketing. In 2022 alone, spending on alternative data jumped over 35% to $3.4 billion as the chart below illustrates:
What‘s driving this surging interest? Simply put, alternative data empowers more informed decisions. By combining datasets like credit card transactions, mobile usage, micro-climate readings and shipping container volumes, businesses and investors uncover real-world trends far faster than government indicators or quarterly reports, delivering an instant informational edge.
Sources of Alternative Data
Alternative data emanates from a vast ocean of previously untapped sources that now data technology renders within reach. Key categories include:
Web Activity
- Search trends
- Website traffic
- Ecommerce transactions
- Social media posts
Mobile Location and Usage
- Navigation activity
- App usage
- Customer journey patterns
Internet of Things (IoT) Data
- Connected vehicle statistics
- Smart home appliance usage
- Industrial sensor readings
Orbital Data
- Satellite imagery
- Shipping data via transponders
- Climate and soil analytics
Business Operations Data
- Retail foot traffic
- Supply chain monitoring
- Company email receipt volumes
And innovations like computer vision and drones expand these datapoints daily. IDC estimates over 2.5 quintillion bytes of data gets created each day from these sources. Taming this firehose to serve business needs launches the imperative for honed analytics capabilities.
Analytics Techniques for Alternative Data
Converting torrents of unstructured data into investable insights requires advanced analytics workflows.
Dealing with Data Diversity
Messy formats must become computable. Images should transform into metrics via computer vision. Natural language processing (NLP) extracts text sentiments and topics. Forex chatroom messages can quantify future rate moves. Object recognition in video feeds might track store traffic or inventory.
Time Series Modeling
Temporal patterns matter with fast-moving alternative data. Analysts must pinpoint trends, cycles and seasonality across timeslices using ARIMA models to forecast activity. Markov modelling helps predict next states.
Ensemble Modeling
Combining outputs from multiple diverse models outperforms any one. Regression trees, SVM, neural networks and more can vote on conclusions to avoid overfitting and noise.
Causality vs Correlation
Spurious correlations between unrelated variables frequently emerge from alternative data. Sound statistical testing must determine true causal links and contributory drivers.
Programming languages like Python and R contain libraries supporting these techniques purpose-built for alternative data at scale using distributed approaches where necessary.
Building Data Infrastructure to Manage Volume and Velocity
The sheer torrent of alternative data inundating organizations makes architectural decisions vital.
Handling Streaming Data Velocity
Trillions of datapoints gush continuously from GPS pings, anomaly detectors and inventory barcode scans. Architectures like lambda and Kafka enable real-time data collection and routing to analytical targets.
Storing Structured and Unstructured Data
Petabyte-scale structured data with defined schemas rests in cloud data warehouses like Snowflake, whereas data lakes on object stores accept images and texts. Managed services tame complexity. Hybrid lakehouses combine both.
Achieving Flexibility Via the Cloud
Scaling elastically to meet surges, while minimizing wasted resources, proves possible only via cloud infrastructure for most. Multi-cloud mitigates vendor dependence and allows geographical data residency.
DataOps For Smooth Orchestration
With intricate chains spanning data arrival to DecisionOps, DataOps heritage helps manage interlinked microservices. API-driven functions chained by tools like Airflow prevent brittle point solutions.
While every organization‘s data build varies, separating storage, compute and orchestration facilitates agility. Consultants like AIMultiple help navigate architectural strategy.
Operationalizing Signals from Alternative Data
Alternative data must ultimately steer decisions through widespread analyst access. Streaming outputs tied to operational triggers turns analysis to real-time action.
Analytics-Based Alerting
Anomaly detection on supply chain trackers may issue purchase alerts. Stock volatility models could activate automated hedging. Mall occupancy counters may start marketing campaigns.
Embedding Intelligence Into Apps
Integration layers like Tableau, PowerBI and Looker blend alternative data within BI tools and custom apps to reach employees. AI assistance enhances natural interfaces.
Automating Downstream Workflows
Taking human delays out of conclusions from alt data analysis using workflow automation ensures rapid time to value. RPA bots enact mundane processes while intelligent document processing handles unstructured data.
Alternative Data in Practice – Applications Across Industries
Innovative organizations across sectors creatively harness alternative data analytics today:
Financial Services – Hedge funds pioneered alternative data tactics. Data types like satellite imagery inform projections of big box retail revenue for stock picks. Foursquare data quantifies foot traffic to predict earnings surprises and lending risk. Natural language processing of financial news calculates market sentiment.
Retail – Following anonymous mobile shoppers‘ journeys exposes in-store conversion friction. Data informing shelf inventory levels and pricing helps perfect assortments and margins. Site traffic volumes estimate local demand across outlets.
Manufacturing – Sensors monitoring vibration, temperature and pressure prevent costly outages. GPS and RFID offer provenance tracking. Satellite data aids demand planning. And climate data fuels crop yield modeling for commodities.
Healthcare – Wearables data helps tailor wellness interventions. Clinical trial data assessments can accelerate drug development. And combining sentiments, geographic and demographic data sharpens patient marketing.
The applications are endless. With the right data strategy, any industry can tap alternative sources to outflank the competition. To discuss options tailored to your organization, schedule a consultation with an alternative data advisor here.