by Lou Agosta

Prepackaged business intelligence (BI) and data warehousing (DW) systems have evolved and grown along with the enterprise resource planning (ERP) applications that they leverage for BI reporting, advanced analytics and actionable business results. Such prepackaged software is also sometimes called “BI in a box.” While such a slogan is a concise expression of an engaging overall vision of breaking open the shrink wrap and getting a functioning BI application with minimal effort, it significantly understates the complexity of the BI, DW and ERP system design and implementation dynamics. Even if the vision is a sound one, like most visions there are trade-offs and choices to be made. Let’s look at the major ones.

Reinventing the wheel is hard work. One major advantage of a prepackaged business intelligence system is that it leverages design and implementation skills from expert software development professionals. Most client (“end user”) enterprises are in the business of retail, finance, manufacturing, distribution, insurance, and so on, and do not aspire to be software development specialists. Many business processes – especially in accounting and finance, HR and supply chain management – are well defined and clearly understood. If a packaged BI system provides about 80 percent – or more liberally, more than half – of the functionality needed for BI, then it is a good bet, if not a bargain.

This is especially the case if an enterprise falls in the mid-range of size – say, between $50 million and under a billion dollars (US) in annual revenues. In such mid-sized firms, basic business processes are sometimes in flux as the firm grows. Such emerging processes can be expected to benefit from the predefined structure provided by a package, which, after all, brings with it an architecture and implied business process flows. A purchased packaged and its architecture is arguably less flexible than one that is custom designed and built to accommodate the proprietary business process that represents a given firm’s competitive advantage. However, the choice is usually not off-the-shelf architecture versus custom architecture. The usual choice is off-the-shelf architecture versus accidental or ad hoc legacy systems or no coherent architecture.

However, this also implies a trade-off. If an enterprise, regardless of size, has a highly customized business process – whether customer scoring or lifetime value in basic data warehousing, demand planning in supply chain management, or cross selling recommendations – it is a roll of the dice that a given prepackaged BI system will capture the design points that enable such a competitive advantage. It is unlikely. If the package did capture such a competitive advantage, then all that a competitor would have to do would be to acquire the package and the competitive advantage would be available market-wide. This may not be a show stopper, since, as noted, many design points and processes are common within a given industry vertical in finance, human resources, inventory control, shipping, sales and marketing, and so. Yet smart client enterprises will do their homework up front, performing a readiness assessment and an inventory of their own information assets, rather than purchase a prepackaged system as a solution to their own ill defined problems = x. This rarely occurs.

Indeed the recommendation is to apply as few customizations as possible to any package that is purchased. Keep it simple. Follow the package design points and processes as provided more-or-less out of the box. Why? When the package eventually needs to be upgraded – either due to technology or business progress – then all the customizations will create a significant upgrade and version control effort. Absent a compelling, even urgent business need, avoid customization.

Thus, a strong case can be made for not reinventing the wheel and leveraging the design expertise of the software industry in delivering prepackaged BI applications. Other critical criteria in making a decision include:

Fit the front-end metadata to the back end.

The key term here is “metadata” – a term that usually causes the eyes of business executives to glaze over. Nevertheless, it is a critical path to success in leveraging the value of a prepackaged solution. For example, if an enterprise is operating an ERP system from SAP, Oracle, or Microsoft, then look for technology with metadata that enables the back-end ERP system to be easily and rapidly configured by the BI presentation layer. In other words, do not expect a system designed to work with Microsoft Dynamic AX to provide visibility to proprietary SAP business application process interfaces (BAPIs). This is common sense; but it is also due diligence.

Perform a readiness assessment.

Prepare an inventory of types of data stores – including multiple legacy data stores and back-end ERP systems. This will tell you how many different types of connectors (also called adapters) will be needed to access the diversity of data stores that may need to be integrated to put the “intelligence” into “business intelligence.” The fundamental limitation of any package is that an organization must modify its BI process to accommodate the package, rather than the package conforming to the already existing, in-house business intelligence process (assuming, of course, that such a process does exist – which is often not the case). For a majority of commercial enterprises where project management and or software development are not a core competency, prepackaged BI (and its data warehouse) offers a compelling, though qualified, value proposition.

Ask to see the data model.

Sign a nondisclosure if necessary. Does the model fit the needs of your enterprise? This is not a trivial question and it may not be able to be answered without building a quick and dirty prototype. Ask the vendor for support in doing so. The vendor will respect you, even if it means more work. Does the data model work for dimensional modeling? For example, a basic example would be the data cube answering the question: What customers are buying what produce or service and when and where are they doing so and at what cost? Such a cube leads to dozens of different decision points about supply chain optimization, customer lifetime value, and market dynamics. Devoting effort to assessing the fit and usability of the data model is rewarded at implementation time by fewer surprises.

Assess the usability of the interface.

Usability, usability, usability. How are dashboards, reports, and ad hoc queries configured and shared? Can the business analyst take care of her- or himself, performing end-user self-service or will a work request to the information technology (IT) department be required? If the client enterprise is a global organization or aspires to be one in the near future, what are the multi-language and multi-currency capabilities of the frontend?

Business intelligence in the cloud.

A major trend is to get out of the business of operating business intelligence systems (and any related data warehouse) on site at the enterprise location. BI in the cloud can be a compelling value proposition for rapidly growing small and mid-sized enterprise that choose to put their energies into the product or service, not their IT infrastructure. In general, the start-up costs are less, though the total costs over the long term can be greater, since the cost of the infrastructure is necessarily captured by the vendor over a shorter period of time. As noted above, trade-offs are the order of the day. If your enterprise goes this route, insist on an explicit service level agreement (SLA) that guarantees timely, workable provision for ownership and transfer of all enterprise data if the client and hosting vendor decide to part company.

Prepare the business and technical staff for the organizational changes.

These changes are not always explicitly recognized but are definitely implied by installing and using a BI package. Such an initiative can be an empowering one – but only if the staff is ready to take responsibility for engaging in the work of autonomous decision making and new opportunities for professional collaboration and communication with both customers and colleagues. If the culture is one of the business staff being given a fish rather than fishing for themselves, then significant training and enrolling in the new paradigm of end-user self-service will be worth its weigh in gold, taking the enterprise to a new level of cooperation, collaboration, and velocity in decision making.

By Dave Menninger

Cloud computing is having an increasingly large influence over the IT landscape. It is likely that, whether you realize it or not, corporate data exists and/or is migrating outside the walls of your organization. Recent research by Ventana Research shows that in areas such as customer services, sales, and workforce or human capital management, software as a service (SaaS) or cloud-based applications increasingly are being accepted and adopted. In our benchmark research on business intelligence and performance management, for example, only 53 percent of organizations prefer their systems on-premises, and we expect that percentage to decline in the next 12 to 24 months, in which more than one-third of organizations plan to begin using cloud-based or SaaS applications.

However, cloud-based applications and services raise information management challenges that don’t necessarily exist in on-premises deployments. The new silos of applications and software that enable doing business “in the cloud” also are new corporate data repositories that must be integrated with other enterprise data and must be managed as a whole. Among the many challenges lurking inside the cloud are data accessibility, data consistency, data integration, data quality, and data governance.

In many cases, the advocates and buyers for using cloud-based services are line-of-business managers who see such solutions as addressing their immediate concerns for rapid deployment with minimal capital outlays. But these business folks may not be aware of the data challenges associated with moving to the cloud. For instance, as more and more data resides in applications managed by third parties, how will the organization bring it all together for analysis, reporting, and other necessary uses? Without a capable data integration infrastructure, will users be forced to cut and paste data from reports or export it to spreadsheets, encountering the issues of consistency and accuracy that practice raises?

The proliferation of cloud-based data and applications has implications for the movement of data into and out of the enterprise. When a line of business goes to a cloud-based application, it must migrate its data about employees, customers, products, and other essentials to the associated cloud-based application. Since some applications are likely to reside on the premises, some portion of the cloud-based data may need to be brought into the enterprise as well. Once data resides in multiple locations, challenges arise in data synchronization from system to system in different locations – in the cloud and locally. In this case, the consistency of data used by various people at various times may come into question, causing costly errors in business decisions or inefficiencies as personnel spend time reconciling different sets of information.

When their data resides outside the firewall organizations also must rely, at least in part, on the cloud providers for adequate data governance and security. As business advances its use of software as a service and managed services in areas such as CRM, ERP, BI, and others outside of IT, our research shows only 12 percent have deployed data governance to this area; an additional 18 percent had plans to do so within 12 months. That leaves more than two-thirds who have not tackled data governance in the cloud. When it comes to relying on the third-party providers, only one-third of organizations are very satisfied or satisfied with current efforts to support data governance. Clearly a significant gap exists where organizations need to embrace data governance no matter where data is created, stored, and used. Master data management systems would be similarly impacted as well.

Some vendors have begun to adapt their on-premises information management products for cloud-based data. Other vendors have emerged to focus purely on cloud-related data issues. The market for cloud data integration products and services is still emerging. We have learned some lessons in the on-premises past that will be applicable to the cloud, and established vendors are aggressively pursuing these market opportunities through a combination of development efforts and acquisitions. We also see new vendors entering the space, each with their own unique capabilities. One common theme I hear repeated by large and small companies alike is that cloud data integration is about frequent, smaller transfers of data rather than large bulk operations. I’ve also observed that none of the cloud-only vendors offer all the functionality of fully established on-premises solutions.

Marketplaces, another phenomenon associated with cloud-based applications, if successful can help level the playing field between new and established vendors. A marketplace provides a venue where third-party applications can be shared with the user community for a particular product or vendor, effectively expanding the vendor-provided capabilities. With the proliferation of cloud-based applications and data sources, both the need and the opportunity exist for connectors to these different sources. Our research indicates that organizations are already integrating on average five or more different data sources. As more applications are delivered as services, this number is likely to rise.

Even the largest vendors will struggle to support all the different data sources organizations need to access and integrate. So in addition to evaluating the technical merits of different cloud-based solutions, it’s also important to understand how active the marketplace is surrounding the product you are evaluating.

Your organization will need to address another key question specific to the cloud: public versus private. Most of the discussion of cloud-based products and services centers around the public cloud platforms such as Amazon’s Web Services. However, private clouds offer an alternative with many of the benefits of public clouds while minimizing some of the concerns about security and service levels. In my experience, while private clouds may address these key concerns they lag behind public clouds in delivering core benefits such as automatic provisioning and elasticity.

As an industry we’re just beginning to understand the challenges and opportunities that are unique to the cloud. It’s important to understand the issues that are driving purchases of cloud-based solutions. Combined with an understanding of IT’s concerns about cloud-based deployments, we can develop strategies that align these two sets of requirements.

Author Dave Menninger is VP and Research Director for Ventana Research.

by Eric Kavanagh

Old Man River just keeps on rolling. Every year, the Mississippi rises. The dividing line of our Continental United States swells each Spring with the currents of North American tributaries large and small. In a world of remarkable unpredictability, of this one perennial reality, we can remain quite sure.

Certitude is something the markets love, something most people need in order to sleep well at night. While almost nothing in life is ever certain – save death and lots of taxes – still, the encouragement provided by recurring patterns helps keep the home fires burning in even the coldest financial winters.

Which brings us to an overwhelming question: Why not harness the natural power, the eco-mastery of this world wonder? After all, the Romans built aqueducts to propagate the nourishing gifts of water througout their growing empire… which lasted more than a millenium. Why shouldn’t we?

Obviously, engineers and other experts would need to map out the specifics, but the broad strokes are clear: Create overflow aqueducts at various points along the Mississippi’s route to offload the excess flow created each spring. Connect these aqueducts where appropriate, both east and west of the river.

Let’s consider the up sides to this plan: 1) protect cities like St. Louis, Memphis, Natchez, New Orleans and others; 2) create tens of thousands of jobs for years to come; 3) deliver invaluable water to otherwise drought-prone, agriculturally significant lands; 4) save millions of Louisiana oysters!

Seriously, Texas is going through a major drought right now, resulting in rampant wildfires across the Lone Star State. And during any given year, lack of rain causes pain and misery in any number of Midwestern states. Why not spread the wealth of American water beyond the center of our nation?

And the down sides? Human intervention does cause issues, no doubt. There will be environmental impacts. But there are impacts already, including loss of wetlands in Southern Louisiana, which threatens New Orleans. Still, placing more control valves along the Mississippi will provide options.

Were this system now in place, we would not fret about the loss of property, the risk to life, the potential for great American cities to flood. We would be celebrating the cycle of nature, thanking our lucky stars, and preparing for the bounty of goods that would result from all that additional water.

Let’s get back to the basics. Instead of subsidizing fee-happy consumer banks that almost went belly up by risking their (and our) capital on complex derivatives, why not finance a solution that even ancient peoples understood as central to the prosperity and longevity of countless generations?

If we’re in the age of Big Government, let’s make some big things of use. Say what you will about big-ticket federal spending, the Hoover Damn is darn cool, and it continues to serve as a wellspring of value for a significant portion of the USA, providing jobs, energy and a serious stream of tourists.

An inspiration to Mark Twain, one of the greatest writers to grace our country, the mighty Mississippi is the aorta of America. With enough creativity and a healthy dose of guidance from the federal government, we can mitigate serious risk while giving our economy a shot in the arm. Thoughts?

Progress Software has always been a little larger that it looked. Founded around 30 years ago, it was one of the early 4GL/database companies and one of the few that made a life for itself as software moved from mainframe/minicomputer deployments to the client server world and then to n-tier browser-based architectures. Progress Software both survived and thrived. This was achieved mainly  by virtue of good engineering and a dedication to the ISV market.

The Big Footprint

In  the 1990s Progress became the gorilla of the ISV market for ISVs building business applications. It has and still has many thousands of ISVs as customers, all of whom provide regular revenues to Progress. Down there in the SMB market the ISV is often the gate-keeper of  the small business IT budget. The SMBs may not have huge IT budgets, but the dominant ISV in an account will normally determine where that money goes. Given Progress’s business model, (run time license fees) those ISVs never passed huge sums on to Progress, but collectively they controlled a huge IT spend over which Progress had a good deal of influence. For that reason Progress has always been a little bigger than it looked.

As  that pre-millenium decade progressed, more and more ISVs emigrated from other failing 4GL vendors and moved to Progress and that migration continues even now. As far as we’re aware, the only other vendor with a bigger piece of the ISV market is Microsoft.

The Next Decade

Progress was always a platform company, in the sense that it provided a complete development platform – but that platform was targeted at the SMB market. In the past 10 years Progress has gradually changed direction and through a series of acquisitions, coupled with internal development projects, it has built what I think of as a “2 layer enterprise platform.”

In 2000 (over 10 years ago) they launched Sonic which actually defined the concept of an Enterprise Service Broker (ESB) – the idea being to have a software component that managed inter-program messaging throughout all or part of the corporate network.

In 2002 it acquired eXcelon Corporation (formerly Object Design, an object database company) and soon after acquired a UK company, Apama, which was the first stream processing software development company. It had a 4GL-like capability that allowed financial traders to easily develop and implement trading algorithms. It was paired with the Object Design database, ObjectStore, and now delivers event processing (real time) capability across the board. eXcelon’s XML technology was migrated to Sonic, enabling it to do XML translations on the fly.

In 2006 Progress acquired Actional Corporation, which had had one of  the few (some would maintain the only) true enterprise class SOA management product aimed at  process monitoring, security, and implementing run-time governance. Also in 2006 Progress acquired Neon Systems, which had mainframe modernization software. In 2008 Progress acquired Xcalia, a data integration company, and Mindreef, which had web services testing and diagnostic software. Also in 2008, it acquired IONA technologies which had long provided a CORBA infrastructure but also offered some open source SOA components and Artix a commercially-licensed SOA product. Finally, in 2101, Progress acquired Savvion, a respected provider of Business Process Management technology.

For 10 years it wasn’t exactly clear what Progress was doing. It was acquiring a crowd of very good software components, but it wasn’t at all obvious (to me at least) that these components had coherence until Progress started filling in the gaps.

The Problems with SOA

SOA was always a work in progress to some degree. By adhering to web services standards and with the help of an ESB you could get some useful reuse out of some of your software,  and you could thread applications together to build end-to-end processes, but there were bits missing. At  the architectural level, these included a true data integration layer and a full SOA management capability. At the business process level, this included a full Business Process Management (BPM) capability.

If you take a detailed look at what Progress has been doing, it now becomes clear that it has been building exactly that – a true comprehensive enterprise architecture and a true comprehensive BPM capability. The upshot of this is that Progress has started to get  aggressive in the enterprise  market. It now competes head-to-head with Oracle, IBM and Tibco, arguably on an equal footing. And despite the fact its competitors have been established in  the enterprise market for far longer, Progress is winning business. Indeed, this is  the area of Progress’s business that is currently growing fastest.

The Progress marketing pitch is now about architecture, both at the application level and at the business process level and it has the software needed to deliver that.

Companies rely heavily on accurate data, from customer relations to how much product is in inventory. But many struggle to merge data management practices with business processes. The result: bad data.

On the April 28th edition of DM Radio, entitled Data Quality as a Catalyst for Lowering TCO, hosts Eric Kavanagh and Jim Ericson tackled the problem of bad data with Forrester Analyst Rob Karel, along with guests Daniel Teachey of DataFlux, Oliver Claude of Informatica, and Steve Sarsfield of Talend.

There are, of course, acceptable levels of bad data. Different types of business, and in fact various departments within the same enterprise, can tolerate a different threshold of bad data. A high-risk industry, such as health care, certainly has a lower threshold for bad data than a relatively low-risk direct marketing company.

While it may be convenient to have an industry standard available in order to justify data quality levels, Rob Karel says that an enterprise should never look outside itself to come up with a metric. “You have to determine as an organization what tolerance do you have across all the different use cases that are consuming the data; and for each one, they’re going to have a different tolerance level,” says Karel.

Teachey agreed: “What we’ve seen customers do is internal audits and taking an understanding of just what sort of mess they’re sitting on, and how that translates into a more meaningful win.”

When deciding whether or not to leverage a Data Quality solution, companies must ask themselves: What is it costing to do nothing? Steve Sarsfield uses the example of hand-coding. If one guy in IT is developing all the code, tweaking it to accommodate growth, and poorly documenting those changes, what happens when that guy leaves the company? With the headache of trying to pick up where he left off, the next step might be an open-source or commercial data quality solution.

One of the key challenges of initiating a good data quality solution is that tends to be IT-driven, even though the business side will reap the benefits. Karel estimates that 60-70% of data governance initiatives are being driven by CIOs, primarily because they are the first to become aware of the organizational interdependencies with respect to data quality. But while a CIO has the expertise of data collection and management, he is not in a position to decide how to run the business.

“It’s OK for the CIO of an organization to drive the governance initiatives,” Karel says, “but they can’t own the definitions and measures of success.” That’s where the CEO comes in, or some other C-level executive.

To persuade those senior executives to financially and logistically support the idea of data quality, Sarsfield suggests an approach they can identify with. He explains that it always comes down to three things: revenue, efficiency and compliance.
“I think what you need to do is profile early and often,” says Sarsfield. “Someone once said something about metrics: without metrics, you’re really just a person with an opinion.”

And while everyone has an opinion, defining those metrics is a task best suited for the C-level executive, whose key interest is in lowering total cost of ownership (TCO) and ultimately raising the return on investment (ROI).

How are these metrics ascertained? Oliver Claude says it’s essential to link existing business process initiatives with the data side, and make that link visible to the people who are interested in improvement. “It’s about making sure there’s more synergy in defining a joint ROI and understanding the dependencies more fully from the point of view of the customer,” he said.

Karel suggests that companies must move from data-centric to process-centric. The goal is to get data management, data quality and business process professionals to understand their interdependencies. In this bottom-up approach, department or functional managers first decide what the critical processes are. They next look at how their data has been managed and determine if it supports or undermines those critical processes.

In a top-down approach, C-level executives are already fully aware of the value of data quality and data governance, and they drive change throughout the enterprise. Either way, the bottom line is that data governance cannot be treated as a one-time initiative – it needs to be embedded into the business process. For improvement to take place, all levels of the company must have access to the business process metrics and be aware of the scope and consequence of bad data.

“Bad data is endemic of a bad business process,” said Teachey, who notes that a business process glitch can be rectified simply by looking at bad data.
Another benefit to using a data quality solution is its forward-looking component. According to Karel, many business solution applications don’t offer much flexibility beyond their core value. Because data quality initiatives are pervasive across so many different parts of the organization, however, you can build a pretty compelling story if you have the gumption and support to do so.

Data quality solutions, said several speakers on the call, amount to a cost of doing business these days. Integrating and implementing such solutions typically requires both strong leadership and structure, and at the same time, must involve every significant aspect of a business.

“Data governance is an integral part of a data quality program,” says Claude. But getting people to agree on how to govern data is easier said than done. “One of the biggest barriers is the fact that the different organizations across the different lines of business have to be able to collaborate.”

Let’s try to answer this question in a top-down manner.

A great deal of data lives in computers; exabytes of it. Recent estimates published by Caltech suggest that the world generates 2 exabytes of data per year, but that figure is itself growing. The amount of data we store grows by about 60 percent a year and there’s no end in sight. It just keeps on growing. Every now and then we have to invent a new “largest measure of data”; megabyte, gigabyte, terabyte, petabyte, exabyte, zettabyte and the very latest word in data volumes; yottabyte. A yottabyte is a billion billion megabytes. Right now there are no yottabytes of data, but there probably will be in a few decades.

The words “data”, “information” and “knowledge” don’t quite convey the utter importance of data within an organization. It is, in many ways, the life blood of an organization.

Before computers existed we kept information on paper mainly, but also stored it in photographs or on film. In those days we stored a lot less data, partly because storing it was expensive. Go back centuries, to before printing was invented, and we stored even less data. Books had to be written by hand, so data storage was really expensive. There was probably only a few gigabytes of stored data in the whole world, even counting copies of books. And there were monasteries whose only purpose was to write out new copies of the Bible – Xerox machines of a kind.

Continued here – clink on this link.

Note: This is a posting in a series of data integration postings that are being published by Pervasive Software.

It was Saturday morning. I plugged my iphone into my Mac to charge it up. And I left it to charge. After the battery was shown as fully charged, I was politely informed by iTunes that there was another version of the iPhone OS (and firmware I suspect).  Should I load it?

Apple frequently informs me of upgrades and I always take them. Nothing ever seems to go wrong. It’s been that way since I switched to the Mac in 2004. Saturday was the exception.

How My iPhone Became a Brick

The software began to download. I waited. It started loading on the iPhone. Just before it completed it gave me a message.

“Unable to restore iPhone. Error 14 Unknown error”

My iPhone was now a brick. I wasn’t concerned immediately. I just figured it was a random irregularity. I hadn’t jail-broken the iPhone or anything, so it had to be a simple problem. So I tried again. And I got error 14 again. So I went to Apple’s site and read Apple’s suggestion on what to do, such as reboot your Mac/PC then try again, or try it on a different iMac.

I had lost the data on the iPhone, by the way. Once your iPhone is a brick, it gets amnesia and never recovers. You have to reconstitute it. However all data was backed up, so I wasn’t worried.

To cut a long story short, I tried everything Apple recommended, then tried every idea I could find on various iPhone forums. I wasted three hours and all I got was error 14 every time, except once, when iTunes suggested I needed to load different firmware. Well Duh! So I decided to visit the AT&T shop from whence I got the phone.

They were utterly useless. They plugged it it, tried to fix it and gave up after 5 minutes. They knew nothing. I was tempted to tell them that “my phone was now a brick so please replace it.” But I didn’t, because they suggested that I visit the Genius Bar at the local Apple chapel, and I knew that if AT&T gave me a new iPhone there would be hassle in getting it configured to my number. So I went to the local Apple Store, only to discover that I wouldn’t be able to get an appointment with an “Apple Genius” until 11.50 the following day. But never mind, a helpful assistant said he’d see what he coudl do and waltzed off with my Phone. He returned 20 minutes later, to inform me that only a genius could fix it. So I booked in for the following day and went home.

How To Unbrick The iPhone

When I got home, I started to think my way through the problem. I realized I hadn’t done that. I’d just tried every suggestion I’d run into. Most likely the iPhone was corrupted at an OS or firmware level. Quite possibly the download I had originally tried had become corrupt. So, I needed to clean down the phone.

Quite possibly the download I’d loaded was lurking somewhere on my Mac. So this is what I did:

1. I cleaned down the iPhone by putting it in DFU mode (Where DFU stands for Device Firmware Upgrade).
2. I found the download on my Mac and deleted it.

DFU mode. You put an iPhone in DFU mode by doing the following:

• For about 7 seconds keep the “power/lock’ button (top of the phone) and the “home” button pressed – until the iPhone screen goes black.
• Keep them pressed for an extra 2 seconds, then release the “power/lock’ button
• iTunes will then see the the iPhone after about 10 seconds. Now you release the “home” button.
• The iPhone is now in DFU mode.
• You can now reformat the iPhone by reloading everything, but first delete the previous download.

New download. I acquired a valid download by doing the following:

• I went to /library/iTunes/iPhone Software Updates/
• There was a file there which has a name similar to iPhone2,1_3.3.3_7E18_Restore.ipsw. This ipsw file was probably corrupted. So I deleted it. If you don’t delete this, iTunes will try to load it and you’ll have the same problem as before. It all probability, this file is corrupt.
• I restored the iPhone and it worked – because I had reformatted the iPhone and got a fresh update for it.
• Once the iPhone was restored, I reloaded the phone from the last backup.

The only way that this is likely to fail is if the download of the new OS/firmware gets corrupted. So, if it fails, repeat. If this doesn’t work then the odds are that you have a hardware defect and it’s time to get the handset replaced.

The reason I have explained all this is that I couldn’t find an explanation of this on the web. There may be other stuff out there that tells you what to do, but I couldn’t find anything that tells you why you’re doing it.

Last week the German government warned web users to ditch Internet Explorer and go with some alternative (Firefox, Google Chrome or Safari being the obvious choices).

Why?

As far as  I can tell there is a fairly vicious exploit out there which preys on IE version 6.0. It uses an invalid pointer reference to allow it to remotely execute code and hence place a trojan on your PC to steal your information. Microsoft has released Security Advisory #979352, which you can read about here.

The problem only impacts customers using IE6 and while that may still be around 20% of web users, IE7 and IE8 are not vulnerable to this exploit. And even so, to get infected you have to visit a rogue web site with the exploit embedded in it. There are emails in circulation that try to provoke you into doing that. So the risk is there, but it’s not particularly high.

It has to be said that it is not Microsoft’s fault that IE6 users have not upgraded. Many people like myself, who build web sites, gave up trying to accommodate IE6 quite a while ago. It was a bad non-standard release that often generates rendering problems for CSS coders. Microsoft fixed that and moved on. IE6 security was poor as this latest exploit demonstrates. Microsoft will surely produce a fix in time, but Microsoft recommends upgrading or setting Internet zone security in IE6 to high.

So why did the German government suddenly recommend to its citizens to drop this software product?

Even more bizarrely, this morning France has piled in and advised its citizens to drop IE too. Certa, a French government agency that oversees cyber threats, warned against using all versions of the web browser.

What is behind this?

I can only presume that European governments have been spooked by the Chinese attacks on Google and believe that they have to be proactive in order to protect their economies and citizens. However neither government has explained what is wrong with IE7 or IE8. IE8 was designed for security and Microsoft claims that it is the most secure of the browsers.

My advice, until someone demonstrates otherwise is that IE8 is safe, so upgrade unless you were wanting to change browsers anyway.

If a serious vulnerability suddenly emerges in Firefox or Safari, are the French and German governments going to advise you to switch browsers again?

I had a long discussion yesterday about Google’s phone that kicked the ball up and down the street. It concluded in an agreement that the Google phone is a mistake. Here’s the rationale:

• The Nexus One is really not that good, compared to the Droid, for example, never mind comparing it with the iPhone. That’s bad news for brand reasons.
• Google is not a device company, yet and it shouldn’t become one. It’s a tough road. Look at the problems Microsoft has been having with Zune, for example.
• Does Google even have it to become a device company quickly or even slowly. Does it really have the ability, not just to build a phone, but to keep a phone competitive.
• If it becomes a successful device company (which is, I admit, a possible route for it) then it will lose all those companies that are enthusiastically queuing up to build Android devices (cell phones or net books or tablets). They’ll go elsewhere – to Linux probably. The Google app store will be damaged.
• Why put yourself in direct competition with Apple on Apple’s territory?
• Google’s real revenue stream in the mobile market is adverts. That means it needs to inveigle its way onto as many devices as possible (via its app store). A phone of its own doesn’t help.

Google should bury the phone and do what it does best. It should forget about Chrome OS devices too.

Having said that: Kudos to Google for standing up to the Chinese.