Showing posts with label INNOVATIVE GROUPS. Show all posts
Showing posts with label INNOVATIVE GROUPS. Show all posts

Monday, February 12, 2018

Part Three: The Analytics Strategy and Roadmap - A Use Case Driven Plan to Incrementally Build an Analytics Capability Powered by Big Data

In the previous blogs of this three-part series, I addressed a clear analytical divide that has grown in the industry, where relatively mature BI shops are at a definite advantage over most organizations that have yet to fully realize an analytics capability powered by big data. The first blog in this series identified the critical capabilities needed for analytical success with big data, and the many impediments, both technical and organizational, that are holding companies back.
Building on this idea in the second blog, I outlined why the attempt to take a ‘big bang’ approach to big data, by first putting all of the enterprise’s data into a data lake, is not likely to succeed because it returns little ROI in the short run and has major investment, governance, and skills requirements. Instead, I proposed establishing a multiplatform data warehouse environment (DWE) with an architecture pattern that's designed to accommodate immediate used cases with specific goals and measurable ROI, so the program can fund itself along the way.
In this approach, the requisite analytics capabilities will be gained through a managed transformation, an incremental build up in a phased approach, where the big data journey is mapped in clear, achievable but increasingly challenging milestones that induct the different nature and types of big data. The strategic roadmap on big data will be formulated based on these early successes, with more participation and sponsorship of the business when it starts to see value from this technology. That will help refine the tactical aspects of the strategy execution.
In this blog, I present a four-phased roadmap to get there, each phase building the pre-conditions to succeed with the next. The phases will of course overlap when work on a previous phase continues with other use cases. I will cite telecom use cases in the customer experience domain only to illustrate the comparative progression and analytical maturity in each phase.
We have presented a practical roadmap to big data and analytics adoption based on successful practices in industry. This plan presumes nothing and builds on successes at each phase generating the pre-conditions for the next.

The use-case driven approach starts with more technical IT driven challenges and matures eventually to departmental operational decisions and finally to strategic decision support. The maturity looks like this: Data Warehouse Off-Loading, 2) Operational BI, 3) Operational Analytics and 4) Strategic Analytics. The use cases will have to be evaluated in two major dimensions: the implementation capability and capacity needed, and the degree of organizational change required relating to their impact on current business processes.
In the early part of the transformation, the big data initiatives will be more technical in nature and localized at the department level. They will require the least additional skill and have positive, if minimal impact, to business processes. In the later stages, the evolving use cases will have wider business impact and will demand more capacity and technical and organizational capabilities in big data. The final stage involves analytics adoption for use in organizational strategic planning.
As the later stages involve use cases that are more operational and strategic in nature, which can impact processes across many departments, they will demand a more robust organizational change management program to manage the change across different participating groups and additional governance requirements. Large companies will have multiple big data teams, and as the organization builds more advanced big data capabilities, teams will need to come together for interdepartmental use cases.

Phase 1: Offload data and workloads from legacy systems and the enterprise data warehouse


Like most other IT systems, as data warehouses age, their design and enabling technologies can become un-scalable in terms of their economics and performance. Adopting multiplatform data warehouse environments would solve many data storage and performance issues, which is why it is one of the strongest trends in data warehousing today. In this phase, high volume detail transaction data storage and processing will be off-loaded to a Hadoop platform, reducing the storage and computing resource requirements of the relational data warehouse platform. From a business viewpoint, this is a non-disruptive task. It preserves existing investments in data warehousing, and (when done well) it extends the life of an expensive and useful system.
The off-loaded detail data, which is hardly exploitable in a traditional RDBMS will also become amenable to analytic exploitation because of the linearly scalable architecture of Hadoop, increasing the value of these detail data to the business: they will be able to get valuable insights from this detail data with the right questions. Organizations can also explore the possibility of monetizing these detail data. For example, location-based and movement-over-time data can be obtained from Call Data Records in the telecom industry. Inducting mainframe data and/or offloading the processing to Hadoop, active archiving of historical data also is other example of IT use cases for this phase.
This phase will require a relatively small investment in the big data cluster: between 6-10 nodes depending on the data volume to be off-loaded. In terms of investment and ROI, typically this phase will pay for itself in terms of reduction in infrastructure costs, improvement of performance of ETL processes and reports, and in the additional value in detail data.
The foundation of big data capabilities for the organization will be laid in this phase: IT will get a foothold in Hadoop skills on familiar existing structured data. Data governance policies will be applied to the data off-loaded to Hadoop, and in doing that, the finer aspects of practicing the data governance principles and policies will be sorted out, again, on familiar territory of the data. An Agile development methodology with DevOps should be inducted in this phase, delivering value as early as possible while streamlining the support functions to the big data program.

Phase 2: Operational BI (event processing)


While the first phase is based on batch processing, the next will be based on near-real-time and subsequently real-time processing—starting with processing structured data, progressing to semi-structured and unstructured data.
It can start with rule-based event processing use cases on structured data (like fraud detection for telecom), which can happen in near real time, and then move on to processing more voluminous structured data in a more real-time basis (like identifying potential Mobile Switching Center failures and re-routing more profitable customers to a different Mobile Switching Center in real-time to avoid service degradation).
Semi-structured and unstructured data can be inducted for real-time event processing after these successes. Some telecom use cases could include analyzing customer interactions captured by a call center application to identify the key problems customers are complaining about. Sentiment analysis on this data can provide the intensity of customer dissatisfaction around these problems. The text analytics can be further improved by transcribing the recorded calls and using transcripts for this analysis. Further, voice analytics can be applied on recorded calls to measure the customer’s mood associated with the complaints. These analyses will not only provide statistics on overall complaints, but will be able to identify dissatisfied high-value customers in real time.
In this phase, the algorithms are mainly rule-based and fairly deterministic in nature, and the use cases can be limited by actionability and deployment confined to a single department, typically the departments that are showing more traction with the big data initiative, thus improving the chance of building more accurate models and ensuring deployment and use in operations.
The organization will develop the Hadoop data integration skills for different types of data in this phase. They will now have gradually developed a fairly advanced data governance capability and should have established data management policies and processes around it for these more exotic data types. There will be more pervasive use of these data sets by analysts through self-service exposed in analytical sandboxes. The induction of these new data sets will be closely linked with business use cases, data management practice (in terms of data ownership and accountability), ensuring enough data quality, capturing business metadata, security and privacy aspects, etc. Ideally it should not have great impediments and should have the requisite backing from the quarter of the business that will benefit from the use case. The data management process should be formalized through these implementations, developing the requisite controls and artifacts.
These parts of the business will now have adopted the use of big data and would have started realizing benefits out of it. The organization will now be at the “Analytical Practitioners” level. The big data cluster will get much larger with induction of these new high-volume data sources, but ideally it will be funded by the departments deploying the use cases.

Phase 3: Operational analytics


In phase 2, the data lake has been hydrated with varied structured, semi-structured, and unstructured data, and insights have been obtained from them. Typically, these datasets will progressively provide the customer 360-degree view, aggregating data from all customer touch points.
In phase 3, these insights can be combined using advanced analytic techniques to obtain predictive operational intelligence. For example, customer churn models will be deployed based on various types of data obtained on customer interactions in the previous phase. Campaign management algorithms can be refined based on this addition information. Call center data volume in different categories can be forecasted based on historical patterns.
Until phase 2, the big data program was tactical and bottom-up. Now it needs to be met with a top-down strategy to be effective at this next level. The input data as well as actions out of the insights from the use cases will typically span across departments. Hence, the big data program will need to have strategic direction and sponsorship at this phase, ensuring leadership support for identifying which operational areas analytics can be used to improve customer experiences most effectively, and to ensure that the insights obtained drive and enhance the business processes involved.
This leadership is essential for gaining buy-in from managers in sales, service, and support functions applying such insights. Through such leadership, analytics professionals will be able to collaborate with business managers to refine the algorithms and gain feedback about what worked and what did not in applying the analytics in real-world sales, service, and support. Active participation from the business will also be needed in data governance in respect to usage of data and the related privacy issues, which will be more prevalent in this phase. But, success in the previous phases should ideally ensure this participation and sponsorship.
The role of data scientists and domain specialists will become critical in this phase, and the company will have to invest in these skills. The organization is now moving towards being insight driven. Here, the business owners are putting faith in the predications and forecasts from the predictive models, and the organization has the critical skill base and a robust data management capability. The people, the process, the data, and the technology is in place. They have become “Analytical Innovators”. Organizations will catch up with the advantage of competitors and probably break away from them based on the success in this phase.

Phase 4: Strategic analytics


In this phase, adoption of analytics pervades the organization, and the most critical business processes become insight driven. Now the CXOs consult the analytical insights in their decisions, and more strategic decisions also take the big data ‘outside in’ view into account. The enterprise planning becomes more agile by including external drivers derived from the big data, making it more responsive to changes in market conditions and customer behavior. For a telecom company, this would mean analytics driving their strategic planning on product mixes, new products, cell, tower planning, etc.
The gradual transformation of the decision-making culture culminates in use of data to make smarter business decisions to drive creativity and innovation, bringing it to the frontiers of the practice of analytics. At this point, analytics having a huge impact on the bottom line is an established correlation.

The next step in the big data journey


Success with advanced analytics has many daunting pre-requisites that put the relatively mature BI shops at clear advantage, yet an agile management culture tuned to the rapidly changing market conditions is going to be a pre-requisite to survival, if not success, in the next decade—adopting analytics is no longer a choice.
We have presented a practical roadmap to big data and analytics adoption based on successful practices in industry. This plan presumes nothing and builds on successes at each phase generating the pre-conditions for the next. It starts from IT use cases with no business impact, progressing to more and more impactful use cases as the requisite capability develops. This generic and high-level roadmap can be customized for an organization, depending on its business challenges and opportunities, its current analytical maturity, and its internal challenges towards big data adoption.

Thanks to Suman Ghosh from TCS for enlightening us on the concepts.
Source:-
K@run@

Tuesday, November 20, 2012

Bike Riding Tips and Tricks

Now a days the youth are more passionate about their bikes and adventurous rides with it. The bikes and stunts are really a guy thing which drives the riders to crazy fun like nothing else. But they don’t realise the risk underneath their stunts until they are once experienced for. The following tips will be quite useful for the begginers who are going to be a good riders in future. With all senses a rider has to control the following:
 • Brake 
• Clutch 
• Acclerator 
• Signals lights 
• Sharp turns 
• 150 degree view ahead 
With perfection in these the ride will be under control and happy....but lacking in any thing of above may result in severe disasters.. Common mistakes by Riders: 
• Applying brakes while crossing sharp turns which result in skidding of vehicle. 
• Making the vehicle to run down street with engine off. 
• Not maintaining the center of mass of (bike+rider) jointly.
 • Careless ride by consuming alcohol.,etc.
If you can’t turn a crossing sharply then just apply brakes ahead and then slowly make the turn rather than skidding over the road. Riding the bike downwards with engine off makes the rider to loose control over the vehicle.Remember that an engine in On state works greatly than the engine in Off state.The person should understand his bike well enough to maintaine the center of gravity always aligned in correct manner.The following fig shows the difference
By carefull pressuring up your weight on the foot rest will do a great job under sharp turns. Always drive on the right side of the road and for some countries like India you should align yourself on the left side of the road as per the traffic signs and signals.Use hand signals when ever and where ever necessary.
YOUR DEAR ONES ARE WAITING AT HOME, THINK ABOUT THEM AND DRIVE SAFE. K@run@

Saturday, October 13, 2012

From Google documents to Google Drive


  • Download Google drive and enjoy lot more features.......Google apps has been advanced very well in recent days........its good to be a Google fan
  • Html view of the files uploaded,the time of updating the multiple files and the privacy and security....still lot more we have to identify.....main advantage is it is integrated with our gmail thats enough to highly depend on it....

K@run@

Saturday, September 1, 2012

Bar Code matters a lot



Tips to all u frenz...Always Keep Safe!!
HOW TO READ BAR CODES...(everyone must know)
ALWAYS READ THE LABELS ON THE
FOODS YOU BUY--NO MATTER WHAT THE FRONT OF THE BOX OR PACKAGE SAYS, TURN IT OVER AND READ THE BACK---CAREFULLY!
With all the food and pet products now coming from China, it is best to make sure you read label at the supermarket and especially when buying food products. Many products no longer show where they were made, only give where the distributor is located. 

The whole world is concerned about China-made "black-hearted goods". Can you differentiate which one is
madein Taiwan or China ? The world is also concerned about GMO (Genetically Modified Organism) foods;
steroid fed animals (ex: 45 days old broiler chicken). It is important to read the bar code to track its origin. How to read Bar Codes....interesting !
If the first 3 digits of the bar code are  690, 691 or 692, theproduct is MADE IN CHINA. 471is Made in Taiwan . If the first 3 digits of the barcode are 00-09 then it's made or sourced in USA This is our right to know, but the government and related departments never educate the public, therefore we have to RESCUE ourselves. Nowadays, Chinese businessmen know that consumers do not prefer products"MADE IN CHINA", so they don't show from which country it is made.
However, you may now refer to the
barcode - remember if the first 3
digits are:
890......MADE IN INDIA
690, 691, 692 ... then it is MADE IN CHINA
00 - 09 ... USA and CANADA
30 - 37 ... FRANCE
40 - 44 ... GERMANY
471 ........ Taiwan
49 .......... JAPAN
50 .......... UK

K@run@

Wednesday, August 8, 2012

NASA's newly landed Mars science rover Curiosity snapped the first color image of its surroundings while an orbiting sister probe photographed litter left behind during the rover's daring do-or-die descent to the surface, scientists said Tuesday.



Curiosity's color image, taken with a dust cover still on the camera lens, shows the north wall and rim of Gale Crater, a vast basin where the nuclear-powered, six-wheeled rover touched down Sunday night after flying through space for more than eight months.
The picture proved that one of the rover's key instruments, a camera known as the Mars Hand Lens Imager, or MAHLI, was in good working order affixed to the end of Curiosity robot arm.
Designed to take magnified, close-up images of rocks and other objects, or wide shots of landscapes, the camera currently remains stowed on the rover's deck. But once in full operation, scientists can use it to capture fine details with a resolution as high as 13.9 microns per pixel -- several times finer than the width of a human hair.
"It works. It's awesome. Can't wait to open it and see what else we can see," Curiosity scientist Ken Edgett told reporters on Tuesday.
The latest images were relayed to Earth during the rover's first full day on the Red Planet, following a descent through the Martian atmosphere and touchdown on Sunday night that NASA hailed as the most elaborate and challenging ever in robotic spaceflight.
The $2.5 billion project is NASA's first astrobiology mission since the Viking probes of the 1970s, and the landing came as a much-welcome success for a space agency beleaguered by science budget cuts and the recent cancellation of its 30-year-old space shuttle program.
The primary mission of Curiosity, touted as first fully equipped mobile laboratory ever sent to another world, is to search for evidence that the planet most similar to Earth now harbors, or once hosted, the key ingredients necessary for the evolution of microbial life.
But mission controllers at the Jet Propulsion Laboratory in California plan to put the rover and its instruments through several weeks of thorough checks and trial operations before gradually beginning science exploration in earnest.
They want to be sure the car-sized vehicle and its sensitive components came through the tricky, jarring final leg of Curiosity's 352 million-mile (566 million-km) journey to Mars without damage.
Encased in a protective capsule, the rover blasted into the Martian sky at 17 times the speed of sound and slowed itself using friction from steering through the thin atmosphere.
Closer to the ground, the vessel was slowed further by a giant, supersonic parachute before a jet backpack and flying "sky crane" took over to deliver Curiosity the last mile to the surface at 10:32 p.m. PDT on Sunday (1:32 a.m. EDT on Monday/0532 GMT on Monday).
A day later, NASA's sharp-eyed Mars Reconnaissance Orbiter surveyed the scene from a vantage point 186 miles above the planet and found Curiosity's approach to Gale Crater littered with discarded equipment used to position the rover near a towering mountain rising from the crater floor.
"You can see all the components of the entry, descent and landing system," said camera scientist Sarah Milkovich.
The satellite's "crime scene" image, released Tuesday, lays out the trail of debris beginning about 1,312 yards from Curiosity's landing site. That is where the heat shield came to rest it was jettisoned during descent.
The back shell of the capsule, which contained the parachute, ended up about 673 yards away from the rover. The last part of the elaborate landing system, the rocket-powered "sky crane" crash-landed 711 yards away after lowering Curiosity to the ground on a tether.
Mars Reconnaissance Orbiter's image shows the heat shield in a region dotted with small craters, while Curiosity is surrounded by rounded hills and fewer craters. To the north is a third type of terrain riddled with buttes, mesas and pits.
"If it were up to me I would go to where those three come together, so we could start to get the flavor of what's going on here in terms of the different geologic materials," Edgett said.
Scientists expect it will be weeks until Curiosity begins roving and months before it heads to the 3-mile (5-km) high mountain at the center of the crater, the primary target for the two-year science mission.
Scientists believe the mound, known as Mount Sharp, may have formed from the remains of sediment that once completely filled the basin, offering a potentially valuable geologic record of the history of Mars.

K@run@

Friday, July 20, 2012

BMW_CONCEPT_6


The Concept 6 design team was determined not to let the engine blow out to the party-pooping width of the CBX's imposing donk - and it looks like they've done a good job keeping it acceptably narrow. Each cylinder is still slightly oversquare (its bore is slightly larger than its stroke), which will help it spin up and develop horsepower at higher revs, but the stroke is relatively long compared to the ratios used in BMW's inline fours, keeping those cylinder bores as narrow as possible while retaining the ability to rev.
There's very little space in between cylinders, and the alternator and other electrics have been relocated from the side of the engine back behind the crankshaft in the spot above the transmission. The overall result is a motor that BMW claims is four whole inches narrower than the previous thinnest inline six on the market - and only slightly wider than a big inline four.
With a capacity of 1600cc, and all the extra exhaust headers and gear required by an inline six, it's still going to be a very heavy powerplant, but BMW have used a trick from their K-series sportsbikes to neutralize the negative effects that big lump of metal could have on the bike's handling. With the engine tilted forward by 55 degrees, the main bulk of the cylinder bank is kept low, pushing the centre of gravity down and forward, which should help keep the bike flickable and fun in the twisties.
Peak output will reportedly be similar to the K1300 series engines - somewhere around 170 horsepower - but the big six will belt out a massive 130 Nm of torque from just 2000rpm. For reference, the torque monster Suzuki GSX1400 peaks at about 125 Nm at around 4700rpm. The new engine's torque peak is unspecified, but it should rev as high as 9000rpm, making it a hugely flexible powerplant that BMW believes will be "the ideal power unit for a range of different motorcycles." Yummy!



K@run@

Thursday, July 5, 2012

HIGGS BOSAN---Proton sub particles

Great invention for the decade which gonna change the future......Higgs Bosan was discovered after blasting the protons......many scientists strived so hard for 50 years for this....including our indians....Named as Higgs BOSan after the Indian scientist BOSE
K@run@

Friday, March 2, 2012

Overview of WINDOWS 8

If you have been following all the good press around Windows 8 and are waiting to try it on your own computer, here’s the good news. The consumer preview version of Windows 8 (just a fancy name for beta software) is now available for download and it is very likely that your existing system specs are good enough to run Windows 8.


The System Requirements for Windows 8


According to the Windows 8 FAQ, any machine equipped with 1 GB of RAM, 16 GB of hard disk space and 1 GHz processor should be able to handle Windows 8. The minimum RAM requirements are 2 GB in case you would like to install the 64-bit version of Windows 8.


Should you download Windows 8 Setup or the ISO Image?


As you may have noticed on the Windows 8 download page, the installation of Windows 8 can be done in two ways.


You can either take the easiest route and download the Windows 8 Setup program – that’s also the default option.
Alternatively, you can download ISO Images of Windows 8.
If you are planning to install Windows 8 on your existing computer, either on a different partition (dual-boot) or just want to upgrade an older version of Windows to Windows 8, the default Setup program is a good choice.


Please note that that your installed software program will only be preserved if you are upgrading from Windows 7 to Windows 8. If your planning to install Windows 8 on top of Windows XP or Vista, only the files will be preserved but not the various software programs that you may have on the disk.


The ISO image may be more handy in other situations like:


Your computer has an x64 processor but is running the 32-bit version of Windows. If you want to install the 64-bit version of Windows 8, download the 64-bit ISO.
You have an iMac or MacBook and want to install Windows 8 on the Mac using Boot Camp software.
You want to install Windows 8 on multiple computers. Download the ISO, create a bootable DVD and boot the other system using this Windows 8 disk.
You want to run Windows 8 as a Virtual Machine inside your existing copy of Windows.
You are running Windows XP.
The universal product key for Windows 8 is NF32V-Q9P3W-7DR7Y-JGWRW-JFCK8.


Will my software programs run inside Windows 8?


Before grabbing the ISO image of Windows 8, quickly run this setup utility and it will show a list of all software programs and hardware drivers on your system that are compatible with Windows 8. Else you can visit this page to see a list of all known software that are found to be working with Windows 7.


What route should you take?


You can have Windows 8 on your computer in three ways – you can install Windows 8 side-by-side (also known as dual-boot), as a virtual machine (so that it runs inside your existing Windows just like any other software) or Windows 8 can be your main OS (there’s no going back then).


If you just want to try out Windows 8 but without disturbing any of your existing set-up, the safest bet is to use a Virtual Machine. If you have a vacant partition or don’t mind creating one (it’s easy), go for the dual-boot option. Else, if you have a spare computer, you can consider upgrading to Windows 8 overwriting the previous installation of Windows. Good luck!
K@run@

Thursday, December 1, 2011

GE to Open New Global Software Headquarters in Bay Area, Hire 400 Software Engineers

REVOLUTIONIZE THE MODERN AGE



As the Internet evolved from the dial-up days of America Online to the always-on, cloud-dwelling social network, a parallel development has been taking place in the background: the digital web of the world’s trillions of machines.
Over the last several decades, GE’s software engineers have guided the growth of this emerging industrial Internet. Putting their brains and manufacturing skills to the task, they connected jet engines, power transformers, and medical devices to boost the efficiency of these complex systems and save customers money. With some 5,000 software engineers on staff, GE’s software revenues are about $2.5 billion and the company expects double-digit growth from now until 2015.
Today, GE announced what would be a new dynamo powering this growth: a new Global Software Center, located in San Ramon, California. The center will hire and house 400 software engineers and other professionals developing digital tools that gather and analyze the millions of gigabytes of data generated by controls, sensors, computers and other parts of the brains of industrial machines. These tools will predict and respond to changes, and guide customers in how to best use their assets.
It’s the kind of work that went into GE’s rail Movement Planner and Trip Optimizer. The program gets locomotives to talk to each other, loop in traffic control systems, freight loaders, and technicians with their smartphones. This is no idle talk: a railroad can increase speeds up to 20%, cut fuel consumption by 10%, and save as much as $200 million in capital and expenses annually.
The San Ramon facility will be GE’s “nerve center for software” and link to other GE businesses and software engineers. Mark Little, GE’s Chief Technology Officer, says that the center will promote collaboration across GE and its diverse group customers. “On any given day, one of our software experts could be working on a clean energy project, while at the same time contributing to a program that improves the delivery of health care,” says Little.

K@run@

Saturday, October 1, 2011

BRAND NAMES

ABN AMRO - In the 1960s, the Nederlandse Handelmaatschappij (Dutch Trading Society; 1824) and the Twentsche Bank merged to form the Algemene Bank Nederland ( ABN; General Bank of the Netherlands) . In 1966, the Amsterdamsche Bank and the Rotterdamsche Bank merged to form the Amro Bank. In 1991, ABN and Amro Bank merged to form ABN AMRO.

Accenture - Accent on the Future. Greater-than ‘accent’ over the logo’s t points forward towards the future. The name Accenture was proposed by a company employee in Norwayas part of a internal name finding process (BrandStorming) . Prior to January 1, 2001 the company was called Andersen Consulting.

Adidas - from the name of the founder Adolf (Adi) Dassler.

Adobe - came from name of the river Adobe Creek that ran behind the houses of founders John Warnock and Chuck Geschke .

AltaVista - Spanish for “high view”.

Amazon*com - Founder Jeff Bezos renamed the company to Amazon (from the earlier name of Cadabra*com) after the world’s most voluminous river, the Amazon. He saw the potential for a larger volume of sales in an online bookstore as opposed to the then prevalent bookstores. (Alternative: It is said that Jeff Bezos named his book store Amazon simply to cash in on the popularity of Yahoo at the time. Yahoo listed entries alphabetically, and thus Amazon would always appear above its competitors in the relevant categories it was listed in.)

AMD - Advanced Micro Devices.

Apache - The name was chosen from respect for the Native American Indian tribe of Apache (Ind), well-known for their superior skills in warfare strategy and their inexhaustible endurance. Secondarily, and more popularly (though incorrectly) accepted, it’s considered a cute name that stuck: its founders got started by applying patches to code written for NCSA’s httpd daemon. The result was ‘a patchy’ server รข€” thus the name Apache.

Apple - for the favourite fruit of co-founder Steve Jobs and/or for the time he worked at an apple orchard. He was three months late in filing a name for the business, and he threatened to call his company Apple Computer if his colleagues didn’t suggest a better name by 5 p.m. Apple’s Macintosh is named after a popular variety of apple sold in the US. Apple also wanted to distance itself from the cold, unapproachable, complicated imagery created by the other computer companies at the time had names like IBM, NEC, DEC, ADPAC, Cincom, Dylakor, Input, Integral Systems, SAP, PSDI, Syncsort and Tesseract. The new company sought to reverse the entrenched view of computers in order to get people to use them at home. They looked for a name that was unlike the names of traditional computer companies, a name that also supported a brand positioning strategy that was to be perceived as simple, warm, human, approachable and different. Note: Apple had to get approval from the Beatle’s Apple Corps to use the name ‘Apple’ and paid a one-time royalty of $100,000 to McIntosh Laboratory, Inc., a maker of high-end audio equipment, to use the derivative name ‘Macintosh’, known now as just ‘Mac’.

AT&T - American Telephone and Telegraph Corporation officially changed its name to AT&T in the 1990s.

Bauknecht - Founded as an electrotechnical workshop in 1919 by Gottlob Bauknecht . BBC - Stands for British Broadcasting Corporation.

BenQ - Bringing ENjoyment and Quality to life.

Blaupunkt - Blaupunkt (Blue dot) was founded in 1923 under the name Ideal. Their core business was the manufacturing of headphones. If the headphones came through quality tests, the company would give the headphones a blue dot. The headphones quickly became known as the blue dots or blaue Punkte. The quality symbol would become a trademark, and the trademark would become the company name in 1938.

BMW - abbreviation of Bayerische Motoren Werke (Bavarian Motor Factories)

Borealis - The Northern Lights or Aurora Borealis, is the celestial phenomenon that features bursts of light in colourful patterns dancing across the night skies of the north. Borealis, inspired from the shining brilliance of the Northern Lights, was formed in 1994 out of the merger between two northern oil companies, Norway’s Statoil and Finland’s Neste.

BP - formerly British Petroleum, now “BP” (The slogan “Beyond Petroleum” has incorrectly been taken to refer to the company’s new name following its rebranding effort in 2000).

BRAC - abbreviation for Bangladesh Rural Advancement Committee, world’s largest NGO (non governmental organization) . It works in development programs around the world.

Bridgestone - named after founder Shojiro Ishibashi. The surname Ishibashi (?) means “stone bridge”, i.e. “bridge of stone”.

Bull - Compagnie des machines Bull was founded in Paristo exploit the patents for punched card machines taken out by a Norwegian engineer, Fredrik Rosing Bull.

Cadillac - Cadillac was named after the 18th century French explorer Antoine Laumet de La Mothe , sieur de Cadillac, founder of Detroit, Michigan. Cadillac is a small town in the South of France.

Canon - Originally (1933) Precision Optical Instruments Laboratory the new name (1935) derived from the name of the company’s first camera, the Kwannon, in turn named after the Japanese name of the Buddhist bodhisattva of mercy.

CGI - from the first letter of Information Management Consultant in french (Conseiller en Gestion et Informatique) .

Cisco - short for San Francisco . It has also been suggested that it was “CIS-co” — Computer Information Services was the department at StanfordUniversityt hat the founders worked in.

COBRA - Computadores Brasileiros, “Brazilian Computers”, electronics and services company, was the first state-owned designer and producer of computers in the 1970s, later acquired by the Banco do Brasil.

Coca-Cola - Coca-Cola’s name is derived from the coca leaves and kola nuts used as flavoring. Coca-Cola creator John S. Pemberton changed the ‘K’ of kola to ‘C’ for the name to look better.

Colgate-Palmolive - formed from a merger of soap manufacturers Colgate & Company and Palmolive-Peet. Peet was dropped in 1953. Colgate was named after William Colgate, an English immigrant, who set up a starch, soap and candle business in New York Cityin 1806. Palmolive was named for the two oils (Palm and Olive) used in its manufacture.

Compaq - from “comp” for computer, and “pack” to denote a small integral object; or: Compatibility And Quality; or: from the company’s first product, the very compact Compaq Portable.

Comsat - an American digital telecommunications and satellite company, founded during the President Kennedy era to develop the technology. Contraction of Communications Satellites.

Daewoo - the company founder Kim Woo Chong called it Daewoo which means “Great Universe” in Korean.

Dell - named after its founder, Michael Dell. The company changed its name from Dell Computer in 2003.

DHL - the company was founded by Adrian Dalsey, Larry Hillblom , and Robert Lynn , whose last initials form the company’s moniker.

eBay - Pierre Omidyar, who had created the Auction Web trading website, had formed a web consulting concern called Echo Bay Technology Group. ” EchoBay” didn’t refer to the town in Nevada, the nature area close to Lake Mead, or any real place. “It just sounded cool,” Omidyar reportedly said. When he tried to register EchoBay.com, though, he found that Echo Bay Mines, a gold mining company, had gotten it first. So, Omidyar registered what (at the time) he thought was the second best name: eBay.com.

Epson - Epson Seiko Corporation, the Japanese printer and peripheral manufacturer, was named from “Son of Electronic Printer”

Fanta - was originally invented by Max Keith in Germanyin 1940 when World War II made it difficult to get the Coca-Cola syrup to Nazi Germany. Fanta was originally made from byproducts of cheese and jam production. The name comes from the German word for imagination (Fantasie or Phantasie), because the inventors thought that imagination was needed to taste oranges from the strange mix.

Fazer - named after its founder, Karl Fazer.

Fiat - acronym of Fabbrica Italiana Automobili Torino (Italian Factory of Cars of Turin). Fuji - from the highest Japanese mountain Mount Fuji.

Google - the name is an intentional misspelling of the word googol, reflecting the company’s mission to organize the immense amount of information available online.

Haier - Chinese ? “sea” and ? (a transliteration character; also means “you” in Literary Chinese)

HP - Bill Hewlett and Dave Packard tossed a coin to decide whether the company they founded would be called Hewlett-Packard or Packard-Hewlett.

Hitachi - old place name, literally “sunrise”

Honda - from the name of its founder, Soichiro Honda

Honeywell - from the name of Mark Honeywell founder of Honeywell Heating Specialty Co. It later merged with Minneapolis Heat Regulator Company and was finally called Honeywell Inc. in 1963.

Hotmail - Founder Jack Smith got the idea of accessing e-mail via the web from a computer anywhere in the world. When Sabeer Bhatia came up with the business plan for the mail service, he tried all kinds of names ending in ‘mail’ and finally settled for Hotmail as it included the letters “HTML” – the markup language used to write web pages. It was initially referred to as HoTMaiL with selective upper casing. (If you click on Hotmail’s ‘mail’ tab, you will still find “HoTMaiL” in the URL.) HSBC - The Hongkong and Shanghai Banking Corporation.

Hyundai - connotes the sense of “the present age” or “modernity” in Korean.

IBM - named by Tom Watson, an ex-employee of National Cash Register. To one-up them in all respects, he called his company International Business Machines.

ICL- abbreviation for International Computers Ltd, once the UK’s largest computer company, but now a service arm of Fujitsu, of Japan.

IKON - copier company name derived from I Know One Name.

Intel - Bob Noyce and Gordon Moore initially incorporated their company as N M Electronics. Someone suggested Moore Noyce Electronics but it sounded too close to “more noise” — not a good choice for an electronics company! Later, Integrated Electronics was proposed but it had been taken by somebody else. Then, using initial syllables from INTegrated ELectronics, Noyce and Moore came up with Intel. To avoid potential conflicts with other companies of similar names, Intel purchased the name rights for $15,000 from a company called Intelco. (Source: Intel 15 Years Corporate Anniversary Brochure)

Interland - a web hosting provider formally known as Micron Computer, Inc. which was named either after InternetLandor the combination of the largest acqusition it performed, Interliant with the word Land.

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