Advancements in technology and rapidly increasing access to information are enabling customers to be better informed, dramatically shifting the balance of power from businesses to the consumer.
By R. Kamath
Data has long been a problem in asset and wealth management, but the problem has been largely ignored, worked around or swept under the corporate carpet. Lately, however, companies are realizing how critical it is to the success of their operations to have easy access to high-quality data.
Business executives face tough questions every day. Many of these questions don’t always have easy or straightforward answers: Which analytical investments and strategies really increase revenue? What pilots should I run to test data monetization ideas out? What small data or big data monetization strategies should I adopt? At the root of these queries is the one billion dollar question facing organizations everywhere: How do we monetize our data?
Over the past few years, several trends have appeared on the scene thanks to underutilization and the complexity of managing growing data sprawl. Among those trends is Data-as-a-Service (DaaS).
More than a few industry experts are bracing themselves for a possible shakeout of Big Data companies in 2013. Many think it’s inevitable. With this potential shadow looming, how do you, as an enterprise customer, prepare for it? And, while you’re at it, what strategies can you adopt to take advantage of the situation?
In the interest of roadmapping Wall Street priorities for this year, we recently met with MDs and leading architects in various banks and financial services firms. What we got from those meetings is an inside look at what kinds of analytics projects these organizations are investing in; they include Anti-Money Laundering (AML) monitoring, trade surveillance, and Know Your Customer (KYC) analytics. The investments around those analytics in 2013 include:
Information is the lifeblood of every enterprise. Companies today are creating and capturing more data than ever before. The explosion of data has led to many unique and interesting challenges.
Real-time reporting (RTR) is, in theory, a strategic marriage of technology, capability, and process that allows a company’s stakeholders to access data – sales numbers, stock prices and financial reports, for example – on an as-needed basis. In reality, near-time reporting is the best most organizations can do, but it’s nevertheless quickly becoming part of the regulatory landscape, thanks to the new rules imposed by the Dodd-Frank Wall Street Reform and Consumer Protection Act that change how much and what kind of financial information is made public.
LiquidHub has defined a data discovery approach to solving the complex information aggregation challenges companies are facing. This approach flips the traditional approach around; Rather than a large upfront initiative to develop data warehouses and enterprise data infrastructure, it begins with creating targeted business dashboards from the existing information available within the firm.
Pharmaceutical manufacturers, medical device companies, and in reality, any treatment protocol in healthcare is facing an important juncture where “buyers” of these products are demanding a better and more precise analysis of effectiveness of their protocols. Globally, institutions are being set up to leverage what is being termed “Real World Analytics” to capture and analyze data that exists outside of controlled clinical studies.
by Jerry Smith
A principle consideration of most companies is the growth of revenue and margin, the top and bottom line. Just look at the modern day enterprise and one can find a wide variety of valuation-generation capabilities, ranging from innovation centers to product management. But a deeper look reveals that many are myopically focused on creating or improving their products and /or services, while woefully neglecting a rich source of value hidden in the simple zeros and ones of their massive data repositories. But why?
by Jerry Smith
Too many organizations believe that data migrations are an enterprise modernization program necessity …. only to learn too late of their costly and risk prone natures. Most Fortune 1000 businesses can ill-afford the 80% failure rates associated with today’s enterprise data migration activities. They find it hard to absorb the lost opportunity