What do companies need to do to take advantage of Big Data? With the increase of intra and extra business data sources, the volume of data increases, considering also the high frequency with which they are collected, we have at our disposal at all times: a high number of information, often unstructured or unrelated among them, which make the task of those who must manage Big Data and real time analytics particularly challenging.
In this highly entropic context, the industrial Internet should aim at improving business processes and launching an industrial IoT project, identifying the needs of business managers and trying to understand the real value that the IoT can bring in terms of business.
Data analysis in the Industrial IoT must focus on the automation of industrial processes. Thanks to the analysis of data coming from the machines (either using simple visualizations or more complex machine learning algorithms), industrial processes can be automated by developing sets of business rules that are activated whenever an event occurs. Only with the perfect understanding of industrial processes can we develop rules to automate them.
The analysis given in the ‘Internet of Things’ must be able to provide strategic information to understand the rules of production and to be able to act as effectively as possible.
Therefore, the task of consulting in this area is to identify the needs of business managers, verifying how and if new trend technologies can lead to an improvement in business processes. To achieve this it is necessary that the new business intelligence or business analytics systems promote the governance of the system and therefore allow the control, scalability and flexibility of an integrated and complex environment and consequently lead to greater efficiency, also productive. In this way the investment in this area, especially that of big data, finds its justification.
Currently the main software vendors on the market are offering a wide range of technological products unimaginable until a few years ago that modify the paradigm of a classic architecture of data warehouse or business intelligence, solutions that offer direct connectors to the data source and that, using models “In memory”, “columnar” and “high data compression”, allow to avoid the onerous replication of data on additional databases allowing a considerable architectural simplification.
But this context that would seem “smart” should not drag the choice of internal IT that must always have as its orientation the improvement of the specific business of the company where it operates.
It is essential, in the analytics world, to focus not so much on the object to be analyzed but on the data management platform that allows a proactive use of any data (structured or unstructured) that circulates on the Net or in the company.
The 5 trends of Big Data analytics
According to a new report by Gartner in the next few years there will be a strong growth in the automation component of the analytical platforms, with an increase of over 40% of automated Analytics processes; this will allow greater dissemination of Analytics solutions and growth of Big Data.
In this future scenario, these are the 5 trends that, more than any other, will characterize the ecosystem of data analysis.
1 # Big Data: Combining Data to Reduce Size
In order to gain insight and get value from analytics as quickly as possible, companies need to find new algorithms for combining large data with smaller ones , so to reduce the amount of data on which analyzes are performed; in this case it will also be easier to detect false or incorrect information.
2 # Hybrid platform management
The advancement of the cloud will lead to different platforms on which data reside: but data retention on local premise will continue for a long time. 2019 will see the hybrid and multi-platform cloud as a key player in data analysis models, which means workloads and publication will be on cloud and on premise.
3 # Self-service analysis for everyone
More and more data visualization tools will be available at low cost, or even free, making data analysis affordable for everyone. This will facilitate the dissemination of data literacy and consequently the dissemination of Analytics solutions.
4 # Scalability
With the replacement of reporting platforms, the new models will open the self-service data analysis to more people and will be able to meet different needs based on scalability, performance, governance and security.
5 # Analitycs integrated into the new Apps
The new applications must allow all users of the App to be able to explore their data to support the specific situations and tools used for data analysis.
Big Data Management: It’s time for marketing automation
The increasing digitization made available in recent times pushes brands to become smarter! Business Intelligence and Big Data Management on the one hand, on the other hand connected and communicating objects through technology able to reason with new converging strategies.
It is the time of marketing automation that, between email marketing, social management, proximity marketing, univocal identification, personalized loyalty programs, digital payment systems and accessions to unprecedented couponing initiatives, explodes the concept of customer centricity, reaching a personalization of mass like never before!
To date, the mode of implementation of multi-channel communication initiatives, sees 78% of personalized communication on targets and 22% non-personalized; brands must therefore aim at a coherent communication design on all channels, capable of managing the performance of the customer experience, i.e. brand awareness, brand image, loyalty and satisfaction.
In the future, what will differentiate a brand from the other will therefore be the use of smart data. It is no longer just a question of speed but rather of approach: the traditional channel is losing consistency, but not its value.
CRM 3.0, Web, Mobile, email, sensors and interactive installations are all pieces on which retail and production can sew new communication strategies with a high monitoring rate.
The future is data driven and the Mobile Marketing Automation will allow, through instruments of analysis of real behaviors and through advanced communication and engagement strategies, to undertake new strategic actions.
Multichannel, in fact, means being able to intercept the information related to the web experience of each individual customer, allowing to make decisions of relationship and communication in real time to support the business.