Disney, Depp and the cyber supply chain risk management problem

One field-tested security strategy for information systems and digital content is to address the problem through processes, people and technology. On the process front, all companies involved in the production of digital IP should, by now, be adhering to a proven information security framework that fully addresses supply chain risks. That includes making sure your digital IP is protected at all times, even during post-production (or maybe we should say especially during post-production, given recent incidents).

Fortunately, there is a ready-made cybersecurity framework that companies can use, at no charge, thanks to the US federal government, which has done some sterling work in this area, namely the NIST Cybersecurity Framework.

The current version is a great way to get a handle on your organization’s cybersecurity, and the next version, currently in draft, goes even deeper into the need to maintain cybersecurity throughout the supply chain. For that reason, the draft is worth quoting at length:

“The practice of communicating and verifying cybersecurity requirements among stakeholders is one aspect of cyber supply chain risk management (SCRM). A primary objective of cyber SCRM is to identify, assess and mitigate “products and services that may contain potentially malicious functionality, are counterfeit, or are vulnerable due to poor manufacturing and development practices within the cyber supply chain.”

Read more at Disney, Depp and the cyber supply chain risk management problem

Leave your comments below or contact us for discussions.

Share on FacebookShare on Google+Share on LinkedInTweet about this on TwitterEmail this to someone

10 Web Scraping Tools

Web Scraping tools are specifically developed for extracting information from websites. They are also known as web harvesting tools or web data extraction tools. These tools are useful for anyone trying to collect some form of datafrom the Internet. Web Scraping is the new data entry technique that don’t require repetitive typing or copy-pasting.

These software look for new data manually or automatically, fetching the new or updated data and storing them for your easy access. For example, one may collect info about products and their prices from Amazon using a scraping tool. In this post, we’re listing the use cases of web scraping tools and the top 10 web scraping tools to collect information, with zero coding.

Use Cases of Web Scraping Tools:

  1. Collect Data for Market Research
  2. Extract Contact Info
  3. Look for Jobs or Candidates
  4. Track Prices from Multiple Markets

Tools:

  1. Import.io
  2. Webhose.io
  3. CloudScrape
  4. Scrapinghub
  5. ParseHub
  6. VisualScraper
  7. Spinn3r
  8. 80legs
  9. Scraper
  10. OutWit Hub

Read more at 10 Web Scraping Tools

What do you think about this topic? Leave your comment below and subscribe us to get updates.

Share on FacebookShare on Google+Share on LinkedInTweet about this on TwitterEmail this to someone

A Tale of Two Disciplines: Data Scientist and Business Analyst

data scientist and BA

The ability to use data to achieve enterprise goals requires advanced skills that many organizations don’t yet have. But they are looking to add them – and fast. The question is, what type of big data expert is needed? Does an organization need a data scientist or does it need a business analyst? Maybe it even needs both. These two titles are often used interchangeably, and confusion abounds.

Business analysts typically have educational backgrounds in business and humanities. They find and extract valuable information from a variety of sources to evaluate past, present, and future business performance – and then determine which analytical models and approaches will help explain solutions to the end users who need them.

With educational backgrounds in computer science, mathematics, and technology, data scientists are digital builders. They use statistical programming to actually construct the framework for gathering and using the data by creating and implementing algorithms to do it. Such algorithms help businesses with decision making, data management, and the creation of data visualizations to help explain the data that they gather.

Read more at A Tale of Two Disciplines: Data Scientist and Business Analyst

Share your opinions in the comment box below and subscribe us to get updates in your inbox.

Share on FacebookShare on Google+Share on LinkedInTweet about this on TwitterEmail this to someone

How Big Data and CRM are Shaping Modern Marketing

Big Data is the term for massive data sets that can be mined with analytics software to produce information about your potential customers’ habits, preferences, likes and dislikes, needs and wants.

This knowledge allows you to predict the types of marketing, advertising and customer service to extend to them to produce the most sales, satisfaction and loyalty.

Skilled use of Big Data produces a larger clientele, and that is a good thing. However, having more customers means you must also have an effective means of keeping track of them, managing your contacts and appointments with them and providing them with care and service that has a personal feel to it rather than making them feel like a “number.”

That’s where CRM software becomes an essential tool for profiting from growth in your base of customers and potential customers. Good CRM software does exactly what the name implies – offers outstanding Customer Relationship Management with the goal of fattening your bottom line.

With that brief primer behind us, let’s look at five ways that the integration of Big Data and CRM is shaping today’s marketing campaigns.

Read more at How Big Data and CRM are Shaping Modern Marketing

What do you think about this article? We encourage you to share your opinions and subcribe us to get updates.

Share on FacebookShare on Google+Share on LinkedInTweet about this on TwitterEmail this to someone

How to Use Big Data to Enhance Employee Performance

Big Data has been one of the most significant and influential aspects of the Information Age as it relates to the enterprise world. Essentially, Big Data is the massive collection, indexing, mining, and implementation of information that emanates from just about any activity that can be monitored and managed electronically. Some of the uses of Big Data include: marketing intelligence, sales automation, strategizing, productivity improvement, and efficient management.

Enhancement of the workforce is one of the exciting and meaningful benefits of Big Data for the business sphere. Recently, human resource managers and analysts have been researching the implementation of Big Data as it relates to employees, and the following trends have emerged:

Employee Intelligence

For many decades, companies and organizations have tried various methods to gain knowledge about what their employees are really like. The productivity that workers can contribute to their employers is based on personal needs as they are balanced against the performance of their duties. With Big Data solutions, both personal needs and performance can be diluted into metrics for efficient analysis.

Modern workplace analytics originates from tracking employee records as well as metrics on their performance, interactions and collaboration. The idea is to focus on the right metrics to create a climate of positive engagement.

Read more at How to Use Big Data to Enhance Employee Performance

Share your opinions about this topic and subscribe to get updates in your inbox.

Share on FacebookShare on Google+Share on LinkedInTweet about this on TwitterEmail this to someone

A farm-level view on supply chain water risk

Managing any kind of risk starts with good information, but collecting and managing water use data up the supply chain can be a surprisingly tough nut to crack.

Agricultural supply chains are highly complex. Willoughby, for example, sells to four shippers who wash and bag his greens before moving them quickly up the supply chain to retailers such as Walmart and food service companies that supply restaurants, colleges and other institutions all over the country.

At the end of this supply chain, Willoughby’s greens are sold as branded bag lettuces, comingled with other growers’ greens. That means his farm level water use data is averaged in with many other growers’ data.

“The longer the supply chain, the weaker the connection between the farmer’s management information and the ultimate consumer,” said Daniel Mountjoy of Sustainable Conservation, which led a recent tour of Willoughby’s fields.

Inexact water use data is more of a problem in fragmented supply chains such as Willoughby’s, where each link acts independently and contracts are subject to change.

“My shipper may say I need five acres of red lettuce on May 30,” Willoughby explained, “but when May 30 comes around, they’ll say, ‘Actually I only need half of what you grew.’”

That’s because his shippers are at the mercy of restaurants and grocery store chains’ forecasting models.

Read more at A farm-level view on supply chain water risk

Share your opinions with us in the comment box below, and subscribe to get updates in your inbox.

Share on FacebookShare on Google+Share on LinkedInTweet about this on TwitterEmail this to someone