Insights-as-a-Service providers are quick to mention their ability to improve business outcomes because that's the entire point of insights. For example,Capgemini provides Data-as-a-Service, Analytics-as-a-Service, and Insights-as-a-Service options. Data-as-a-Service provides raw data upon which analytical applications are built, Analytics-as-a-Service provides outputs of analyses, and Insights-as-a-Service is linked to tangible outcomes such as revenue increase or cost savings. "I consider them a progression in terms of sophistication and value, and fundamentally what the '-as-a-Service' unit of measure is," said Goutham Beliappa, a leader in the Business Information Management Data Integration and Reporting Practice for Capgemini North America, in an interview.
As information continues to fuel and be fueled by new online channels, we most often hear about the impact this has on the B2C sales world. But as anyone in the B2B space will tell you, this evolution is far reaching and certainly relevant. Similar to B2C buyers, B2B buyers feel empowered by their access to data. As a result of the rise of e-commerce in B2B and the general availability of data on the Internet, B2B pricing and product information is significantly easier to find and compare than before. This is enabling buyers to be armed with more information going into a price negotiation than was previously possible. This also means that buyers now expect companies to have relevant and convenient product and pricing information on their websites.
Data lakes or data hubs -- storage repositories and processing systems that can ingest data without compromising the data structure -- have become synonymous with modern data architecture and big data management. The upside to the data lake is that it doesn't require a rigid schema or manipulation of the data to ingest it, making it easy for businesses to collect data of all shapes and sizes. The harder part for CIOs and senior IT leaders is maintaining order once the data arrives. Without an upfront schema imposed on the data, data lake governance, including metadata management, play vital roles in keeping the data lake pristine, according to experts.
First off, we’re so obsolete in cyber. We’re the ones that sort of were very much involved with the creation, but we’re so obsolete, we just seem to be toyed with by so many different countries, already. And we don’t know who’s doing what. We don’t know who’s got the power, who’s got that capability, some people say it’s China, some people say it’s Russia. But certainly cyber has to be a, you know, certainly cyber has to be in our thought process, very strongly in our thought process. Inconceivable that, inconceivable the power of cyber. But as you say, you can take out, you can take out, you can make countries nonfunctioning with a strong use of cyber. I don’t think we’re there. I don’t think we’re as advanced as other countries are, and I think you probably would agree with that. I don’t think we’re advanced, I think we’re going backwards in so many different ways.
Third party governance programs must evolve to offer more continuous methods for risk assessment and management vs. one and done annual on-site assessments. More and more services are offered through cloud providers that host sensitive information and determining online vulnerabilities on a 24 x 7 basis will become more of the norm for any enterprise interested in managing third-party risk. The other fundamental change in third-party risk is a migration from compliance driven assessments (compliance to a standard) to a risk-driven assessment where risks are identified and managed. Adherence to a standard or framework based on standard practices is better than nothing but not sufficient to manage risk effectively given the evolution of cloud computing.
Probably the key question to ask at this point is do these two overarching digital frameworks play well side-by-side or do they need to be integrated for companies to get the fullest benefits of both? Digital/customer experience is a relatively new phenomenon in terms of realized products and services to support it, so until recently it's been hard to say. But with the maturity of both approaches, I'm now beginning to see digital engagement practitioners have to routinely deal with both frameworks. The result? They find in general that CEM platforms tend to underserve social business needs, while social business frameworks and products often neglect many key aspects of digital experience. This lack of integration leads to more work, lower impact, and a fragmented approach to digital, which is what we were trying to resolve in the first place.
When big names fall victim to data breaches, its big news, making smaller companies believe they aren’t likely to be a target. However, according to Greg Sullivan, CEO of Global Velocity, smaller companies should be on the offensive. “The issue is that SMBs wrongly assume that their size or small influence does not merit attention from hackers or do not educate themselves about potential exploits in their infrastructure,” he says. “While SMBs are not as big as companies like Target and Home Depot, they are the majority of victims at the hands of cyber thieves seeking easy targets. The Verizon 2013 Data Breach Investigations Report found that 62 percent of breaches impacted smaller organizations, likely a conservative figure since not all small organizations are reporting breaches.”
IPSec encrypts data information contained in IP datagrams through encapsulation to provide data integrity, data confidentiality, data origin authentication, and replay protection. The two main IPSec components that are installed when you install IPSec are the IPSec Policy Agent and the IPSec driver. The IPSec Policy Agent is a service running on a Windows Server 2003 computer that accesses IPSec policy information. The IPSec Policy Agent accesses the IPSec policy information in the local Windows registry or in Active Directory. The IPSec Policy Agent then passes this information to the IPSec driver. The IPSec driver performs a number of operations to enable secure network communications such as initiating IKE communication, creating IPSec packets, encrypts data, and calculates hashes.
Whilst the role of a data scientist crosses over with more conventional data analysis positions, there are some stark differences. A data analyst or architect can extract information from large sets of data. Yet they are bound by the SQL queries and analytics packages used to slice these datasets. Through an advanced knowledge of machine learning and programming/engineering, data scientists can manipulate data at their own will uncovering deeper insight. They are not bound by these programmes. Whilst your typical data analyst looks to the past and what’s happened, a data scientist must go beyond this and look to the future. Through application of advanced statistics and complex data modelling they must uncover patterns and make future predictions.
Nothing can stop innovation and as long as this technology brings value then it is here to stay. Traditional ojek may eventually have to become app-based or at least adapt to using their cellphones to get customers rather than wait passively at their posts for passengers. Long-time drivers of established meter taxi companies are not that easy to adapt, with their livelihoods having been tied to a regulated system for so long. The democratized application of Uber is actually unfair competition for them, so it is easy to understand their — and especially the companies’ owners’ — resistance to this innovation. In the end, it would be a new government regulation that decides the fate of Uber and that of public transportation as a whole.
Quote for the day:
"Man is a reasoning rather than a reasonable animal" -- Alexander Hamilton