Hi. Welcome to Ingram Micro.

Please choose your role, so we can direct you to what you’re looking for.

If you’d like to learn more about Ingram Micro global initiatives and operations, visit ingrammicro.com.

4 Ways to Be Better At Big Data Consulting

October 22, 2017

Executives read about the value of big data every day, yet many of them are afraid to tackle big data because they don’t understand how it applies to their operation. The same is true for some VARs – they don’t see the value that big data consulting can bring to their business. Profiting from big data consulting isn’t that difficult if you understand where you can add value and where your limitations lie.

The opportunities for making money in big data consulting continue to grow. According to Tata Consultancy Services, the median spend on big data in 2012 was $10 million, and 15 percent of companies spent $100 million, and 7 percent spent $500 million. Much of that spending is for big data consulting. This is the ideal time for any VAR to take a hard look at big data consulting as a new source of ongoing revenue.

To succeed at big data consulting, you need to make optimal use of your strengths and compensate for your weaknesses. Companies are looking for end-to-end big data solution providers so where you fit in big data is a matter of where you have expertise.

Here are four ways you can become better at big data consulting:

1. Build on what you know

Although big data is the new practice area everyone is buzzing about, it’s not all that new. Big data is part of the evolution of business intelligence and data warehousing. Most of your customers have been using business intelligence analytics and data warehouse programming techniques for years.

What distinguishes big data from business intelligence is the amount of data being analyzed. Although there is too much data and too many different kinds of data to be analyzed using conventional DBMS or SQL tools, the basic principles of data warehousing still apply.

Use what you already know about assembling and analyzing data. Start with what you already understand and use it as a foundation to determine how to tackle big data and determine what you don’t know.

2. Pick your niche

Although customers want someone who can deliver an end-to-end big data solution, big data consulting firms with all that expertise are very rare. Most successful big data initiatives are a collaborative effort that requires consultants in analytics, business, enterprise design, open source programming, and other areas.

Determine where you can offer the most value in the process and use that as your consulting platform. If you have unique expertise in cloud storage, software-defined networking, virtualization, and related areas, offer yourself as an expert in big data architectures. If you understand database programming and have a command of SQL, Java, Python, Ruby, or related scripting languages and are willing to tackle Hadoop, offer your expertise to develop analytics software. If you understand business strategies and how to tie all the pieces together, offer your expertise as a big data consultant and gather the resources you need for the project. This brings us to point number three…
 

3. Don’t try to do it all yourself

Don’t pretend you can deliver every aspect of a big data project (unless you are Accenture). Most big data consulting firms bring specific expertise to the project, such as analytics, social media, programming, cloud solutions, training, or something else to the project. The rest is outsourced.

To profit from big data you can be an expert within one area or the project manager who oversees the project. But be transparent about what you bring and don’t bring to the project. Don’t be trapped by promising more than you have within your control to deliver.

4. Pick your market

Consider focusing on one market area, such as health care, retail, or government. There are plenty of opportunities for big data sales in almost every industry, but unlike other IT sales, customers are looking for experts who can deliver business answers, but just infrastructure, so it pays to know their business.

If you understand the business challenges the customer faces you will have a greater chance of big data success. For example, if you are familiar with stocking strategies, logistics, pricing, and consumer behavior then you understand what retailers are looking for from big data. If you understand security, document tracking, data collaboration, and regulatory compliance, then you can empathize with the challenges that doctors’ offices and hospitals are dealing with.

All big data projects start with a business problem, so understanding the dynamics behind the probe is an excellent place to start demonstrating value.

Just remember that big data is a collaborative effort between you, the customer, and your fellow big data experts. Teamwork is vitally important so be prepared to share your expertise and defer to the experts when needed. To be better at big data consulting, it’s always best to know your limitations.