Data are now key factors for every sectors and functions in any size of company. Every sector and department couldn’t strike without dealing with data. So, Bigdata is playing an important role in the improvement of a company. The use of Big Data is to retrieve important and useful information from the large amount of unstructured or semi structured data.
Bigdata is one of the most trending word in today’s market. The effect of big data in every business- from fortune 500 enterprises to start-up’s is so huge that each and every company wants to leverage it. It doesn’t matter, in which field you are working and what is the size of your company? Data collection, analysis and implementation impact your business in several ways. This is the time where you can’t ignore big data analytics and if you are still saying that ‘Big data is not beneficial for my company’ then you are definitely moving out from the competition.
Can I outsource big data to vendors? Before going to the answer of this question let us look at the different terms used in this question i.e. ‘Outsource’, ‘Big Data’ and ‘Vendors’.
What is outsourcing? Outsourcing refers to the contracting with another company for business purpose. It can be international and domestic contracts. Sometimes outsourcing also refers to exchange or transfer of employee and assets between different firms. It helps the firms in reduction of cost and improvement in quality.
Today, retail is driven by data and technology. Big data is becoming really important to retailers. Retailers must adopt big data and digital skills to get succeed in a sector. According to a survey from “101Data”, 96% of retailers reported that big data was important to them and 48% of retailers reported that big data best fit with their marketing department.
As we know that the thumb rule of online retail marketing is: to know every product across your service area, to know every person to whom they interact and with having the best ability to connect them in a transaction.
We all have probably seen the big data and digital in retail sale. If not then you may experience this. For this you will need to go to a shopping site for online shopping. Add a watch in your cart and after sometime remove it from the cart. Now move out from that website. After onward every site you visit may found a watch ad of that shopping site. Online retailers use the data of your interest and customize the ad to you according to your interest. As a research of Amazon states that they had 30 percent of sales due to their recommendation engine. That is the use of big data and digital in the retails.
One of the famous example of taking advantages of big data by a company to drive success is Rolls-Royce. As we now that Rolls-Royce is famous to manufacture large engines which generate a large amount of power generally used in airplanes and ships. They generated a large amount of data during the manufacturing of a jet engine. They used these big data information in mainly three areas i.e. design, manufacture and after sales support. After using these data they found huge change in every field of their industry. They were getting more appropriate and best designs, Product went more error free and sales increased
These are the few application of big data and digital in retail sale:
Expected buying behaviour– To find the expected buyers of different products using the analysis of data. It’s like if a retailer has to sell a game then they will love to advertise for keen gamers and with the help of big data they may easily find those people.
Opinion about brands– To find the famous product among the buyers and organise their product on the basis of buyer’s choice. It also help us to get real-time opinions & responses.
Personalized Shopping– To provide discounts based on past shopping details like preferences and give discounts on the basis of their previous transactions. It help any organization to keep their customers for a long period of time.
E-Commerce optimization– In retail marketing customers are on driving seat. Companies are totally dependent on what customers want, it doesn’t matter what you sell if it’s not according to the customers need you will never get success. So, it’s essential to understand the user behaviour on the website to optimize sell. Big data analysis can provide the user behaviour.
Optimizing the store– Have you ever noticed that why essentials are at the far end and luxury goods at the start. This is the optimizing store. Using big data analysis they track user movements to understand their behaviour.
Price– Big data can also provide the base for prize optimization model.
Big data is the biggest reason for getting success in retail sale. It creates a lot of opportunities for marketing and sales. So, retailers are moving quickly into big data. Some companies are already using big data and digital and getting benefits of using big data and digital in retail sale and they got 5-6 percent increment in their productivity rates and profitability.
Today Big Data is changing the way of our thinking. It’s changing the way of living and working. We are leveraging Big Data in our growth so that everyone can contribute and take advantages. The big data analytics makes life easier and more goal centred. Analysing huge amount of data gives us more accurate decision making ability. With these benefits it is also affecting our social life. Our social life can revolutionize after applying the big data analytics. There are many area from which Big Data can revolutionize social welfare. I am listing out some of them with reasons that how it can revolutionize social welfare.
Online life will be safer– Now a days everything went online. Our life is almost dependent on online services. From Shopping to Education, Transaction and many more we used online services. But this method is no more so safe. Others may hack your information and misuse those data. Big data can help us in this problem. By analysing the hacker’s pattern it can improve the security of your website.
Education– Today’s education cost is rising twice than any other sector. So we need to find an alternative of these traditional education system. Big data can help us to provide these study materials online. So that all could have easily access to the education.
Health Care– The most impact of big data on our social life is in healthcare sector. It helps doctors to find the pattern of any disease and on the basis of that pattern medicines for that disease can be invented.
Transport- The advantage of big data is also in transportation. In transportation there are multiple of uses of big data from analysing the traffic to road safety and security purpose. Data scientists can find the behaviour of people on road. By analysing the transportation data the pattern of accidents can be identified and their solutions can be generated.
Career opportunities- There are many websites which help job seekers and employees to find their jobs or employees. Job-seekers find the opportunities according to their skills and employees used to get their best meet on the basis of candidates skills
Business future- To plan the future of our business we need to go for big data analysis. Those business decision will take your business far away from your competitors because those decision will be based on the real experience of your customers.
Weather forecasting- Big data can also help our social welfare in weather forecasting. It will give great benefits to all but specially to farmers because most of time they dependent on weather. So use of big data in this area will revolutionize the whole society welfare.
Big data creates a lot of opportunities for every sectors people just need to catch those opportunities for the development of their own and as well as society. One more great use of big data towards revolutionize social welfare is in anti-poverty programs. Big data helps to create difficult policies for the anti-poverty programs. For these type of applications a large database set is needed and linked to different social data sources to get huge amount of information regarding our social life. Then only we can apply these benefits to revolutionize social welfare.
Small business owner may think that big data is for large companies with big time technology budgets. In reality, it is not. Small business can also stand for big data benefits within available – small budget. A small business needs to look at big data in different perspective as they may not know how to start and where to start or may not know if big data exist in the company.
Big data and analytics has become indispensable for any business to stay ahead in this competitive world. If we look at any small or large enterprise having outstanding financial performance over a period of last 4 to 5 years, all will have one thing in common – all of them leverage big data for their decision support.
What does this mean to a small business? Yes, it is the time to start with a first step – if not started.
Today, most of the small companies know that big data is playing a vital role in success of small company. Knowingly or unknowingly many small size business are missing out the benefits of big data because of some wrong believes. Recent studies states that small business thinks that utilizing big data is too costly. Quite often, it’s not really so. You don’t always need to invest huge money in storage, hardware or not even on resources. You may choose cloud option for storage and outsource it to a right vendor for processing.
Let’s look at some ways a small business can leverage big data
Increased customer focus – Small companies can look at all possible data sources – internal and external data, which can help generating better customer insight. Focus on customer preferences can bring increased customer base, lead conversion and revenue. Big data can help finding these hidden insight which can eventually lead to increased lead conversion.
Generate innovative ideas & New product development – Recent trends shows that companies do not require decades to build a billion dollar business. It all can happen in few years leveraging big data. Big data and analytics play a vital role in this journey of quick growth and increased ROI. A small business need innovative ideas which can bring them out from the common line. With the help of big data and analytics, business can have different and accurate information to make innovative ideas and products. It can help small companies to gain competitive edge in marketplace.
As long as you are not investing on big data hardware and software, it is all about testing the water and check whether you can make better informed decisions and leverage them to stand out in the competitive market place.
Massive data-sets on everything from demographic to social data, weather to GPS data, consumer spending habits to government budgets – many are freely available online – if you know where to look and how to pull it. Also, there are many free big data tools available to make sense of this data.
Hiring right talent according to the need is the key factor for a company to be successful. “A good fit for the job equals a good fit for the company” is one of the most appropriate quote during hiring a resource.
Big data value chain is mainly divided in three steps. They are data integration, Big data development, and Big data analytics. We need different skilled resources for these three different phases. A person should be hired when his skills meets the needs of the requirement. Let’s look at these steps one by one..
- Data Integration– As we know that in Big Data, data comes from multiple sources. Connecting these data from different sources leveraging big data technology through big data lab, Amazon web services etc. for collecting data and ingesting to the operations is called Data integration. Data coming from different sources have to connect with the appropriate technology. We need ‘Big Data Admins’ for this purpose who will able to make connection between these two, they must know how to use different data integration tools i.e. Sqoop, Flume, etc.
- Big Data Development– Data comes from different sources in structured, semi structured and unstructured form. Those data need to be stored in an organized manner so different development tools can read it for processing. We need big data developers for this purpose who knows the different data processing technologies like Hadoop, Informatica, Teradata, etc. Their work is to make the data to be readable by data processing technologies. They should also know about different database in which data will be stored.
- Big Data Analytics– This stage contains data processing and converting the processed data for the decision support. Data analysts and Data scientists work in this phase for analyzing data to find out hidden pattern in the data and build statistical models. One of the favorite definitions for data analyst is “A data analyst is someone who is better at statistics than any software engineer and better at software engineering than any statistician.” – Josh Wills” This one line defines the characteristics and needs of a data analyst. A data analyst must be good at problem solving. Companies generally prefer engineering, statistics or computer science background people for this role.
To summarize, some of the key skills needed for Big data team are as follows:
- Hadoop– It is one of the famous big data working framework. Big data people must know this framework.
- NoSQL– On the operational side of Big data field distributed storage like HBASE are used. To work on these databases NoSQL should be known to the person.
- Statistical analysis– This is one of the important skills to be in a big data person. They should be familiar with different statistical modelling tools like R/Revolutio, SAS, SPSS, Alteryx, Mahout Libraries, Matlab and there are many more
- Data Visualization – Person should be familiar with different visualization tools like Tablueau, Spotfire, Qlikview, Rapid miner, MS Excel, etc.
- Programming language– Person to know the general purpose programming language like c, java, python, etc.
- Problem Solving– A big data person must be good in problem solving. So, they can find the solutions of different problems during the analysis.
Big data is comparatively a new field with a lot of opportunities. During hiring process, Companies need to pay attention to what they wanted and go for that. Though, it is not advisable to find people having expertise in all big data tools in three phases mentioned here and it is not necessary. But, it is important that people have a bend of mind for learning new tools.
Defining, articulating and representing business problems is a crucial initial step in any Big Data initiative. To deliver quick results from big data, it is good to have powerful and well organized analytic capability. And, if not? Nothing to worry. Reach out to a right big data partner who can deliver quick results – this could be a Proof Of Concept (POC). Once recognize the POC is successful and could generate business value – yes, go ahead to the next level.
Always, it is good to have internal analytic team who can work on data to solve problems and help finding innovative ways to serve customer better. Analytics team must have enough and good amount of data and an effective communication to deliver results. They also need appropriate tools according to the size and nature of data to perform operation. Analytic team has to look at big data life cycle – from data preparation to final report/model delivery or including model monitoring, if modelling is a part of final outcome. Each and every stage of the big data journey effects the final result and business impact and hence, it is important to have involvement of data expert – we may call him data scientist.
Companies are investing resources on technologies, operations, training and development of skills. But during the analysing of big data the most important factor is understanding of data and connecting with the business background and leverage them for decision support. If the analyst doesn’t have the understanding of these things then the corporate information doesn’t help them to find out the appropriate solution. For delivering quick results, analyst should pay enough time to understand the data and the business problem and more over the business itself. Analyst should have the understanding of customer issues and according to the issues they have to decide, what can be done about it and what tools to leverage.
Let us review factors that drive success when companies try to deliver quick results with big data. To deliver quick results with big data, we will need to consider some of the these points..
Business Understanding – “If I were given one hour to save the planet, I would spend 59 minutes defining the problem and one minute resolving it,” Albert Einstein said. Before making an attempt to solve any problem, we should step back and invest time and effort to improve the understanding of the question that what we are trying to solve. For delivering quick results, we need to have good understanding of the business.
Strong Strategy – Drive to Solution: To run any successful operation a strategy is essential. There should be a strong strategy having a vision that what needs to be done before starting to analyse the data. The whole big data approach should have a strong and clear vision and drive to final output.
Data understanding – Data is the main and the most important factor during the analysis. Whole analysis is around the data. Analyst should have knowledge to use and structure data according to their needs. Data should be organised and well structured, so that it will be easy to work on that. Data should be clustered according to their logical type. So an analyst will target the focus area for the data operations. The area will be identified according to their impact on business.
Smart analytics team: Not size of the team – but, quality of the team. While recruiting the analyst or statisticians, recruiter needs to look for high problem solving capabilities, and reasoning power of candidates. Candidates should have the skills that – how and why to approach a problem. Engineering background candidates may be a good analyst.
Expertise on Big data tools and technologies– To deliver quick results, big data team should have expertise in big data tools and technology. It will help the big data team to get in the core of data.
In a recent survey of “The Economist Intelligence Unit” which has been done after completion of a big data project, one-half of analyst said that they didn’t had enough structured data to support decision-making, compared with only 28% who said the same about unstructured data. In fact, 40% of respondents complain that they had too much unstructured data
Ability to leverage right tool – Once you have the skilled analyst and right data with a strong strategy, you need to look for the correct technology on which the data would be analysed. Technology acts as a bridge between the skilled analyst and the right data. So right technology is needed to operate those data by the analyst. There are different technology which can be leveraged for this purpose according to the requirement.
Governance – It is very necessary to connect all the resources and technologies as a single unit to deliver quick results. Governing the whole process in well-mannered way plays an important role in delivering quick results. Governance body need to evaluate the team and assign the works according to their potential and skills.
To deliver quick results, start with a POC and ensure that result is out and useful. In order to start the POC, it is necessary to have deep business understanding, right mix of skilled people, ability to choose right tools and techniques with a powerful strategy that makes the result faster and accurate.
‘Big Data’ is the word which appears on everybody’s lips these days. In recent years, there has been a huge hype of ‘Big Data’ which is use to analyse by different companies and vendors to capture meaningful insights from a vast amount of data that can be used to improve business and decision making. When the data is too big, and too diverse to handle in standard database; then it is called big data.
As it is clear from the above that big data is huge collection of data. So, it is impossible to use all that data at a time. You can, however, make use of a small portion of the data that is beneficial for your business.
Unfortunately, many small and medium size companies are missing out on the benefits of utilizing big data because they believe that leveraging big data is too costly and too complex. But the truth is that big data is neither too costly nor too complex. Small and medium size companies can also leverage big data because Big Data solutions have become much more affordable in recent years.
There are many ways by which small and medium level companies can leverage big data. Here are just a few ways small and medium size companies can leverage big data towards their success.
Look for unused data– Small and medium size companies should look for those data which never used in the entire value chain. These data can be their feedback by customers, emails, vendor transaction, and many more. By leveraging these data, we can get some meaning insight that can be used to improve the business – the way it runs and operate.
Look for affordable and effective big data partner– Small and medium level companies can outsource their data to a suitable third party vendor for processing because developing internal capability may not be a wise decision for them at the initial stage. So find an affordable and effective big data partner for your success.
Go for small– If your company is small and medium level; then go for a small start towards big data. After getting some quick positive results from the vendor then only go for big implementation.
Look for the necessity – Small and medium size companies can go for leveraging only those part of data, where analysis is required. Analysing the whole data can be a waste of time and money for them.
Location– Cost is an important factor for any size companies including small and medium size companies while leveraging big data. So, find suitable big data vendors – today there are good small players in the marker out there where you get what you wanted at lesser cost at higher quality and quick turnaround. For eg: leveraging big data is costlier in USA rather than leveraging in India.
Adopt new tools and techniques- For collecting and leveraging big data; use new tools and techniques from the market – essentially freeware.
Every business needs to know the way to success and increased ROI. Leveraging big data is useful for all level of companies. The point is – how you are using and implementing it. According to a survey of Gartner, investment in big data technologies continues to expand every year. They found that 73 % of respondents have invested in big data or have plan to invest in big data in next two years. So, if you are a small or medium size company and thinking that big data is not beneficial for me then for sure you are leaving your boat.
In today’s tough competition, big data analytics is playing a vital role in deciding the winner of the market place. Today’s business is mostly centred on the customers, especially retail sector. So, companies prefer to craft personalized marketing strategy according to the changing behaviour of customers. If ‘Technology’ brought big data concept; then ‘Marketing’ used it most for the organization’s growth.
In a recent survey from accenture and general electric showed that 87% of enterprises believe that with the use of big data, the competitive landscape of their industries will be changed in upcoming few years.
89% of them believes that companies without using big data analytics strategy in the next year, they will lose their market and be as competitive.
73% of the companies are investing twenty percent of their technology budget in big data analytics.
From these results we can imagine the role of big data analytics in an organization. Let’s see how big data analytics can help in competitive growth.
Customer insight – As we know that today’s business is customer centred and customer is the focus. So, companies collect data about their customers from various customer touch points and after analysing those data they understand more insight about customers. Companies who missed these valuable analysis result is nowhere in the competition today.
Personalized and dynamic Marketing– For better increased sale, companies need personalized marketing strategy and it is only possible when companies have detailed information about their customers or potentials.
Improved of customer experience– Big data helps companies to improve their customer experience not only in after sale but also to provide new products to the customers according to their needs.
Innovative ideas– Big data helps companies to develop next generation of products and services. For this, manufacturers are using data obtained from sensors embedded in products to create innovative changes new product development after sales services. Analysis of those data helps them to do some innovative way to serve their customers and delight them. If companies not using these benefits and serving them in traditional way; then they are likely to lose their customer base. Getting a new customer is far tough than holding an existing one. So, you always need to do something new for your existing customers. NOKIA is one of the victim of this case.
Minimize risk- A decision based on the real time data is always far better than that decision which is based on historical data – meaning way old data. If you have no information about the current market and trends, then you are making a decision then there is no guarantee that it will work. But after analysing the behaviour of market and making a decision; then it is likely to have less risk.
Improve internal capabilities – Use of big data make an organisation well organised. Companies can know about their internal capabilities using the analysis of these data and can make decision for the improvement.
In summary, the insights that we collect from big data and analytics can be used in different industries and can be paramount in exploring competitive growth. In the upcoming years we will be the witness of big data and analytics to decide the winner of the competition. So, organizations that are not leveraging big data and advanced analytics for decision making; then get on it; else you may lose your position in the game.