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Find out how your organization can achieve new advantages through the visualization and analysis of real-time data and event streams. Today, leading firms in industries such as financial services, healthcare, energy, telecom, manufacturing, government, and more are capturing insights from data and event streams and delivering real-time analytics for both human and automated decisions.
David Stodder
Sponsored by
Datawatch, IBM
Know your data. With today’s information-driven business projects, no maxim could be more true. Yet many organizations lack fundamental knowledge
about their data—and the situation is getting tougher as “big data” sources grow in size and variety and manual documentation efforts can’t keep pace.
Good data knowledge is critical to defining business objects such as customers and products within and across data sources. Clear understanding of data
assets, data relationships, and how sources map to target schema can be a vital business accelerator. Poor understanding leads to higher costs,
embarrassing mistakes, regulatory errors, and data quality problems that damage daily decision making.
David Stodder
Sponsored by
Dell EMC
There’s a fair amount of confusion about how best to collect, integrate, and preprocess data for the purposes of advanced analytics. Many business intelligence and data warehouse professionals think it’s the same as the traditional ETL practices they have applied to their report-oriented data warehouses for years. And some database administrators think it’s just a matter of dumping large volumes of data into a highly scalable repository.
Philip Russom, Ph.D.
Sponsored by
Liaison Technologies
Key BI industry growth areas are focused on big data, advanced analytics, cloud computing, and supporting mobile workers. When they are marketing and writing about using these technologies, vendors, the press, and analyst organizations usually focus on building new and leading-edge systems and applications.
Colin White
Sponsored by
TDWI and IBM Content
The cloud services model offers much in the way of potential benefits to businesses in terms of efficiency and cost savings. It’s no wonder that many enterprise applications have moved to public, private, or hybrid clouds. Although business intelligence applications have been slower to move to the cloud—usually because of data security concerns—this is starting to change.
Fern Halper, Ph.D.
Sponsored by
Tableau Software
Many end-user organizations are currently commencing or expanding solutions for big data and big data analytics. These organizations want to understand how to approach big data and where they stand relative to other companies, especially their competitors. In late October 2013, TDWI launched its Big Data Maturity Model Assessment Tool, which can help to guide IT and business professionals on their big data journey. The assessment looks at companies across five dimensions that impact maturity, including organization, infrastructure, data management, analytics, and governance.
Fern Halper, Ph.D., Krish Krishnan
Content Provided by
TDWI, IBM, Cloudera, MarkLogic, Pentaho
Predictive analytics is quickly becoming a decisive advantage for achieving desired business outcomes, including higher customer profitability, stickier websites, more relevant products and services, and more efficient and effective operations and finances. Predictive analytics involves methods and technologies to help organizations spot patterns and trends in data, test large numbers of variables, develop and score models, and mine data for unexpected insights. Sources for predictive analytics are expanding to include machine data and semi-structured and unstructured data, making it important to include text analytics and mining in technology portfolios.
Fern Halper, Ph.D.
Sponsored by
Birst, Actuate - now OpenText, Alteryx, Pentaho, SAP, Tableau Software