On Demand
One of the hottest trends today is self-service data preparation. Following the path of front-end tools for self-service business intelligence (BI) and visual analytics, self-service data preparation is aimed at providing nontechnical business users with the ability to explore data and choose data sets to fit their BI and analytics requirements. The goal is to reduce IT hand-holding—an ambitious one considering that, according to TDWI research, in most organizations IT manages nearly all data preparation steps, which can include data ingestion and collection, data transformation, data quality improvement, and data integration. Self-service data preparation thus represents a significant and potentially destabilizing change for IT and the way that IT and business work together.
David Stodder
Sponsored by
SAP and Intel
As the data warehouse environment (DWE) continues to evolve, one of its strongest trends is the diversification of data platforms. A rigorously structured relational data warehouse is still at the heart of the DWE, but it is being joined more and more by other platform types, including data platforms based on columns, appliances, graph, streaming data, and open source.
Philip Russom, Ph.D.
Sponsored by
SAP
“Throw the baby out with the bathwater!”
We hear that a lot. Changing business environments and competitive pressures have driven companies to seek a new edge from innovative technologies such as specialized data stores and the cloud. Today’s business intelligence (BI) and analytics implementation experts face disruptive decisions as they strive to support their business users’ shifting and diverse analytical needs. Increasing volumes and sources of data (on premises and in the cloud), technology adoption, more complex data integration and quality issues, and lower data latencies are just a few of the challenges that must be addressed.
Claudia Imhoff, Ph.D.
Sponsored by
TDWI and IBM Content
Firms in financial services and many other industries are under pressure to improve efficiency, productivity, and decision-making power. For both daily operational and strategic decisions, organizations need to draw insights quickly from quality data so that they can understand and act on changes in markets, regulations, operations, customer behavior, fraud patterns, and the competitive landscape. Financial services firms need to be smarter and faster to survive in an industry where business models are changing and old ways of managing risk are out of date.
David Stodder
Sponsored by
Sisense
The world of marketing and the world of advanced analytics have been winding towards each other for years. TDWI research indicates that marketing is often one of the first areas in an organization that makes use of advanced analytics. Marketers understand the value that analytics can provide to understand customers and the customer journey. Marketing analytics provides insight gathered from data analysis that can make marketing more efficient and effective.
Fern Halper, Ph.D., David Stodder
Sponsored by
SAS
Today's integration complexities are supersized. Businesses must contend with unprecedented volumes and varieties of data at a time of growing IT resource scarcity and aging integration software. Throw into the mix the high demands—and even higher expectations—placed on analytics as a way of driving business performance, and it's easy to see why many integration environments are overwhelmed and underperforming.
David Loshin
Sponsored by
Liaison Technologies
In today’s competitive environment, organizations not only want to analyze the past, they also want to understand the present and predict the future. Likewise, organizations want to gain insights from a wide variety of data, ranging from structured, transactional data and unstructured text to spatially enhanced data or machine data from the Internet of Things. TDWI research indicates that many organizations are at an inflection point with analytics—they are making the move from visualizations and dashboards to more advanced analytics such as predictive analytics, text analytics, geospatial analytics, graph engines,and streaming analytics.
Fern Halper, Ph.D.
Sponsored by
SAP