Jinesh Varia

“A picture is worth a thousand words; a brand is worth a million” - Anonymous.

A great technology platform brand is hard to find. I walked through an expo hall of a technology conference the other day, I found 28 technology platforms I didn’t knew existed. They may be great technology platforms, but they’re not great brands.

The technology platform not only provides a foundation for internal teams to innovate quickly but also provides external stakeholders to build innovative solutions on top. It not only provides an abstraction and hides underlying layers of complexity (hardware, software, data) but also provides an easy self-service interface so others can build value-added platforms on top of it. It provides valuable insights and personalized user experiences to each customer by absorbing real-world data and analyzing it with other disparate data sets. The platform is the nervous system of the technology company and the data it manages is the life blood.

Today, most successful technology companies have a platform that it manages. This technology platform is core to the company’s strategy and helps drive its technology vision. The company’s ability to refine and invent quickly to customer’s requests, experiment with new business initiatives and effectively scale to reach the global audience not only determines its success and its position in the technology industry but also influences the cool-ness factor that entices new technical talent to join the company.

Hence investing in building a technology platform brand is extremely important these days.

What does it take to build a world-class technology platform today? What are the important ingredients of a world-class technology platform and strategies to create a world-class technology brand?

First, you have to hire great people who can build awesome products. There are no compromises on this front. These are prerequisites to build high-quality highly-available platforms that solves real problems or enhances everyday life. If your platform sucks, and you are not doing anything about it and nobody is using it, there is no platform.  No matter how hard you try, you cannot build a great technology brand. That’s obvious. In this blog post, I am assuming that you have smart people in your team and they are building awesome innovative products and services that customers love. There are still a few more things you need to do in order to create a world-class technology platform brand:

1. Evangelism
   Evangelism is based on Passion; Passion is based on belief. We start believing when we realize that what we are evangelizing really changes peoples’ lives. Every “high-octane” employee in a technology company has a potential to become an evangelist for the company! Real evangelism is contagious and it spreads with every “gospel”. This is the key ingredient of the recipe!
2. The Art of Story-telling
   Stories are data with a soul. Evangelize by telling stories – stories that discusses benefits (and not features) of the platform - stories that captures and capitalizes on emerging forward-looking trends in the market, stories that highlights how individuals and businesses can improve productivity, reduce costs, increase speed and performance or whatever you are evangelizing. When you believe in your platform and when you master the art of story-telling, you will start making an impact and build a brand perception that matches the product reality. See Building Powerful Web Applications : a Love Story.
3. Two-way Amplifier
   Every approved spokesperson in the company needs to be a two-way amplifier. Amplify the company’s vision and the ‘Voice of the CEO’ outside the company and amplify the ‘Voice of the Customer’ inside the company. Providing structured feedback about products (new feature requests, complaints, enhancements) to people is as important as telling the world about your technology platform. Being an evangelist, AWS sent me to talk but I was there to listen and learn. After every trip, detailed trip report goes to every senior exec and service owner of the company. Internal evangelism (and getting everybody on the same page) is as important as external evangelism.
4. Maintain a Regular Cadence in the Conference Circuit
   Content is King; Content Distribution is the Queen. Its important to be out there, on field, talking to fans, customers, partners and competitors. Conferences are best place to network. Sometimes the “Hallway Track” is more influential and effective than the session tracks. Keeping a regular cadence of your platform’s latest innovation fresh in the minds of people who regularly attend key technical conferences is important. Share intelligent growth stats and metrics in your presentations that demonstrates the scale of your platform.
5. Invest in the Ecosystem
   None of us is strong than all of us. Partners and community accelerate the value of your platform. Just like eating your veggies AND doing exercise both are important to stay healthy, investing in your platform (scale, new features, ease of use) AND investing in your ecosystem are important to build a successful brand. Not integrating with other technology platforms is not optional. It is essential to integrate with all Social Platforms (Facebook, LinkedIn, Twitter, …), Mobile platforms (iOS, Android, WindowsPhone), Cloud platforms (AWS, Azure, Google,…) and provide out-of-the-box integrated SDKs in all language platforms (Ruby, PHP, Java, .NET,  Python, …) .
6. Reach the global audience quickly
   In the world in which all of us have a short attention span and need updates in 140 characters or less, we need to communicate our idea quickly and convey our message in concise and precise manner. Our world is getting flatter everyday, and hence we have to think global in everything we do. Short succinct videos targeted at a global audience is one great strategy to reach the masses quickly.

A great technology brand tells a story of how it improves lives, transforms the way you do business today and solves real problems. It takes time to build a great brand and hence its important to invest in your technology brand early in the process and above data points are few ideas that can help you build a world-class technology platform brand.

– Jinesh

In the previous posts, I discussed the importance of Big Data and its relationship with cloud computing. In this post, I will discuss how you can leverage the cloud for your Big Data.

To get the most of your Big Data in the cloud and maximize your Return on Analytics (ROA), here are some simple ideas that will help you leverage the full potential of the cloud:

Enhance Your Data

Having good data is always better than having lots of data. Incorrect or inconsistent data might lead to skewed results. For example, when you have to analyze data from hundreds of different disparate sources, inconsistency in structure and format of datasets often lead to biased insight, especially when the data is not transposed or transformed into a common format. In order to get good accurate and consistent data, it’s important to enhance it. Enhancing data typically refers to cleansing, validating, normalizing, deducing and collating the data.

Performing “data hygiene” and cleaning up massive amounts of data is not a trivial task especially when you have disparate sources and large amounts of data collected at different time intervals. One can only achieve a certain percentage of “data enhancement” programmatically through scripts and programs (like running ETL jobs). However, for more enhanced accuracy, you will quickly realize that you need a human eye to validate, normalize or collate the data. Enhancements like identifying contextual similarities between columns (geo code vs. street address) or normalizing catalogs can be done by humans better than computers. You can get access to massive human workforce and split your big job into short tasks like validating the suggestion by computer program, normalizing datasets, mapping data elements, providing meta-data, cleaning up irrelevant data, transcribing audio/video files using the cloud.

Point Your Data Source to the Cloud

When your philosophy is to collect as much data as possible and measure everything, you will need massive storage capacity. When you have to collect and store massive amounts of data, the cloud makes it easy. Cloud storage is scalable, durable, reliable, highly available and most importantly, it’s inexpensive to store and can often be free to upload. Instead of moving data in periodic batches, you can point your source of data (your web clients, log generators, and so on) to the cloud, which brings the data closer to the compute resources for analysis.

Moreover, storing data in the cloud allows you to easily share and collaborate with both your partners and the consumers of your data, because they too can leverage compute and storage resources by the hour. They can analyze and extract relevant information from your data.

Analyze your Data in Parallel using the Elastic Supercomputer

The Open Source Hadoop and its ecosystem of tools bring massively parallel computing to mainstream developers. Hadoop enables the ad-hoc full-scan queries that we discussed earlier. It enables developers to break away from pre-optimized data warehouses and do exploratory analytics.

Hadoop in the cloud gives any developer or business the power to do analytics without the capital outlay. Today, you can spawn a Hadoop cluster in the cloud within minutes on the latest high performance computing hardware and network without making a capital investment to purchase the hardware. You have the ability to expand and shrink a running cluster and decide how soon they need their answers. With some cloud pricing models, you can bid for unused capacity at even lower prices and lower your costs even more.

Companies are realizing that analytics and processing massive datasets in parallel is sweet spot for the cloud and that the cloud doesn’t limit their choice of analytical functionality. You are not limited to using Hadoop; you can run Open MPI or any other commercial tools on your dataset and get better insight. You have the power to choose from a range of different analytics software – The Big Data Stacks – or even use a combination of open source and commercial tools on the same dataset to get the insight you desire and evolve analytics over time. Moreover, the cloud is elastic and cost-efficient, while at the same time offers a range of price and performance alternatives that can be tailored to how soon we need an answer. It’s a truly elastic supercomputer.

Access Aggregated Data in Real-Time with a 2-Tier Processing Model

Delivering business insight whenever you need it across massive amounts of data is not easy. To optimize results, many companies leverage a 2-tier processing model. First, they use a Batch Tier to analyze massive datasets in parallel, and store the aggregated data in separate data store (Query Tier). This pattern has two advantages. First, it leverages the power of the cloud by analyzing the batch in parallel, which greatly reduces processing time. Second, by storing pre-computed data in a NoSQL scalable data store (like Apache Cassandra, HBase, Amazon SimpleDB, Amazon DynamoDB, MongoDB, Riak etc.), continuous querying of the aggregated data is possible. Since the data is automatically indexed on input, it can be queried in near real time. This is especially useful when you want to visualize Big Data.

Conclusion

The cloud accelerates Big Data analytics. It gives enormous power to the Data Scientist – a new and emerging discipline – to work with Big Data, without limits. Since the cost of experimentation is low in the cloud, they can experiment often and respond to complex business questions quickly. The cloud makes it easy to absorb Big Data datasets and process them in parallel, and offers a variety of Big Data Stacks to choose from. Customers can choose to apply the technology most appropriate for their needs.

Most importantly, moving your Big Data to the cloud allows you to gain more insight from the data quickly and at a price point unmatched by older technologies.  The cloud provides instant scalability and elasticity and lets you focus on analytics instead of infrastructure. It enhances your ability and capability to ask interesting questions about your data and get meaningful answers. This changes the game.

- Jin