Challenge Your Data
Push harder. Move faster. Innovate. The tools are here to make it happen.
New business challenges and the technical innovations to which they give rise are continuously transforming the way businesses are run. Whenever humans improve a tool to better serve a well-known need, they inevitably discover unsuspected applications and profitable new opportunities.
That’s the situation today in business intelligence (BI), where an impressive array of capabilities has recently been introduced to address operational and technical challenges. The most enterprising users are adopting these new tools to find and exploit previously untapped business opportunities. Teradata Magazine talked to a number of industry experts to get the latest on where the big revenue-generating opportunities are. They cited four key areas to keep an eye on.
A Cure for Analytics Memory Loss
Challenge: Since the dawn of the database, historical analysis has been a major hassle. Until recently, however, most data warehouses didn’t conserve history except for transactional data. When a value changed in another type of record, the old value was overwritten and lost. There were workarounds for historical reporting, but they were manual, labor-intensive, slow and expensive. A great deal of potentially valuable analysis has never been done because it was simply too much trouble.
“Every organization has some need to look at trends across time periods,” explains Dave Stodder, director of research and BI at TDWI. “A data warehouse can be really helpful if it’s modeled and organized to store and manage data history.”
Solution: New temporal solutions offer an optional time-awareness feature. Now when a value in the data warehouse changes, the old value is automatically saved along with a record of when it changed and the period during which it was valid.
Opportunities: “Temporal data support in the warehouse makes time-dimension analysis faster, easier and more consistent,” Stodder says. “But it also opens up many new types of analysis that just weren’t possible before.”
- Companies can normalize sales reporting as territories and customer assignments change over time, revealing the true performance of the sales force and its management.
- Manufacturers can easily analyze product quality issues using the actual bills of materials in effect on the date of manufacture.
- Insurers can quickly and accurately process claims based on the policy terms in force at the time of the loss event, not as they may have been amended by subsequent changes.
- Analysts can test quantitative models on market data from different periods and assess their performance against known market outcomes.
Enriched Location Analysis
Challenge: Until recently, location data was hard to get and harder to analyze. Now, with GPS technology embedded in all types of devices and services, it’s possible to know the physical location of customers, business assets, even business events—often in near real time or as they change over time. Unfortunately, most geospatial data sets are very large and exist outside the data warehouse, making combined analysis with other business data impractical. Practical applications have been limited and specialized—for example, oil and gas exploration and geographic information systems (GIS).
Solution: New innovations bring geospatial data directly into the warehouse so it can be managed and analyzed together with business data, enabling a unique combination of business analytics enriched with geospatial data and geospatial analytics enriched with business data.
“Location is part of almost every other data element we analyze ... So if you can collect data on its locations you can do location-based spatial analysis ...”
—Dan Vesset, Vice President of Business Analytics, IDC
Opportunities: “Location is part of almost every other data element we analyze,” says Dan Vesset, program vice president of business analytics at IDC. “If it’s a building it’s in a certain fixed location. If it’s a mobile asset or a customer, it has a current location and probably a variety of other fixed locations associated with it. So if you can collect data on its locations you can do location-based spatial analysis, and there are a variety of use cases for that.”
- Network operators can use geospatial analysis to identify geographic areas of lower service quality—high rates of dropped calls, failed connection attempts, etc. By mapping these areas against existing network facilities, they can target and prioritize investment prospects to optimize their impact on capacity and service quality.
- Insurers can incorporate geospatial information in their risk calculations to identify and mitigate geographic concentrations and optimize pricing for known geographic risk factors such as flood, earthquake, landslide or tsunami exposure.
- Retail and hospitality marketing companies can analyze customer residence locations in relation to existing facilities to understand travel distances, prioritize new facility selection and target marketing campaigns.
- “Trucking companies are using geospatial analysis to track their fleets, optimize routing and dispatch efficiency, and reduce fuel consumption,” Vesset explains. “If they see a vehicle that isn’t moving for an extended period they can call the driver and identify the problem. At least one company has demonstrated real savings in fuel consumption.”
Discovering Hidden Gems
Challenge: “The simple fact is that our information ecosystems are putting out much more information than they used to,” says Shawn Rogers, vice president at Enterprise Management Associates. “They’re coming at us at fire hose velocity and volume, much faster than most data warehouses are designed to handle. There’s value hidden in these massive data flows, but if we want to do analytics on them we’re forced to create new architectures that support it.”
Solution: New analytical platforms deliver massively parallel processing for very large, highly varied data sets. These platforms are ideally suited for discovering significant events, patterns and relationships in large, diverse data sets, allowing high-value data to be identified and selectively brought into the data warehouse to enrich and extend core analytics.
“There’s value hidden in these massive data flows, but if we want to do analytics on them we’re forced to create new architectures that support it.”
Enterprise Management Associates
- Businesses can detect and prevent fraud by conducting on-the-fly analysis of transactions, interactions and systems, allowing them to block malicious users, networks and programs.
- Companies can analyze complex patterns using click-through and search data. Combined with historical behavior trends and demographic data, this can help marketers know exactly where to place advertisements on a page for the greatest response.
- Social analytics uncovers deep social relationships and interactions hidden in raw transaction data, online behavior and social networks to gain behavioral insights, target influencer marketing and analyze content within the social network.
- A wireless network operator can analyze years of call records to identify and prioritize high-value targets for capital reinvestment. It can also analyze the records of calls that were dropped or terminated and identify locations associated with substandard service quality.
Keeping Hot Data Affordable and Cold Data Accessible
Challenge: Innovations in the analytics sphere have dramatically reduced data access times, but the high cost of such solutions, relative to older, slower products, poses a challenge for data warehouse administrators. Typical practice is to put the newest and most frequently accessed data on the faster flash products, and the least used data on lower-cost disks, which tend to be slower. The challenge lies in monitoring usage, then allocating and moving the data. It’s not a task anyone wants to attempt manually.
Solution: Unique hybrid storage management automatically place the most frequently used data on the fastest, solid state storage and the least used data on the slowest storage without user or administrator intervention. As data use frequency changes over time, it is moved automatically to the appropriate storage location.
“We can do so many things today that we could never do before. … And I really believe we’re just getting started.”
Opportunities: “Because I can access data faster, I can now begin to do things I couldn’t before,” says Donald Feinberg, vice president and distinguished analyst at Gartner. “I might be able to do real-time repricing or risk analysis. I might be able to catch credit card fraud at the cash register, not three weeks later.”
- “Airlines reprice the seats on their flights all the time,” says Feinberg. “They have a target yield for each flight, and every time they sell a seat the yield calculation changes—or it would if they could run the pricing model quickly enough. In most cases they can only do it once or twice a week. But if they could run that calculation faster, they might be able to reprice nightly. And if they could put all that data in memory, as expensive as that might be, they could probably reprice after every sale.”
- With the ability to continuously analyze large amounts of current business data, manufacturers can reduce their decision-making turnaround time from hours into minutes or seconds. This helps them optimize their allocation and pricing on the fly.
- New analytics solutions can help network providers enhance security measures by spotting and stopping fraud before perpetrators have time to do any damage. Since tracking activity on any one network can translate to an enormous data load, new solutions help providers spot unusual patterns and identify suspected IP addresses faster.
- New solutions provide real-time analysis of customer click activity for by-the-second optimization of messages to help enhance customer spending. Improved marketing, based on a more complete view of the customer, can also decrease the rate of shopping cart abandonment—a rate said to be as high as 50%.
A Wellspring of New Business Value
New business opportunities can be enabled by new innovations in BI and analytics. It’s a well-established cycle that shows no sign of slowing.
“That’s why CEOs and CIOs are spending money to do these types of things,” Feinberg concludes. “Analytics let us match the inventory on our shelves to the demand at the counter, find fraud as it occurs, resolve quality issues before they ruin a customer relationship. We can do so many things today that we could never do before. Our ability to do analysis at operational speed has matured tremendously over just the last few years, and I really believe we’re just getting started.”
Combine focused teamwork with innovative technologies.
With a variety of hot new technologies reaching maturity, 2011 proved to be a great year for collaborative problem-solving for business and IT. Because let’s face it:
No matter how innovative they are, “cool” technologies are truly valuable only when they can help the business solve real problems.
Not for IT Only
“These technologies aren’t enough to deliver maximum value to the business. That can only come from collaboration:
a tight partnership between business users and IT professionals.”
chief technology officer, Teradata
We’re seeing a plethora of emerging technologies that offer potentially groundbreaking business benefits. For example, MapReduce-based advanced analytics tools can increase business users’ flexibility in how they look at data, without knowing in advance which questions they might want to ask. Multi-temperature data management products make it easier for business users to maximize the volume of data they store, for longer periods, at the lowest cost and without sacrificing performance. And new data warehousing tools let users enhance insight by analyzing geospatial and temporal data collected by a proliferation of sensor devices.
Yet by themselves, these technologies aren’t enough to deliver maximum value to the business. That can only come from collaboration: a tight partnership between business users and IT professionals, with a focus on solving business problems as a team. Well-executed, this type of collaboration is like an intricate dance, with applause for the bottom-line benefits it produces.
The best possible pas de deux? The business articulates its vision for changing the way things are done. IT suggests new technologies that can deliver capabilities needed to solve business problems. Together, the two sides design solutions that use the technologies to improve or enable new business processes. Such collaboration helps the team support differentiation and competitive advantage, thereby realizing the vision for change.
All Together Now
Is your business making optimal use of today’s emerging technologies? Can your IT organization use these solutions to help the business move forward on the path to change? Are the teams working in concert?
A wealth of cool new tools and techniques is available to help your business profit and grow. It’s time to make sure your business and IT teams are moving in sync to ensure you gain maximum advantage.