Data Warehousing & Business Intelligence

 Data Warehousing


                                             Data Warehousing & Business Intelligence

Why DW & BI

1. Business intelligence is new management reporting and dashboarding.

2. Data warehousing and business intelligence can help the organizations both proactively and reactively managing areas of concerns and identifying areas of potential.

3. Most of the large setups in India and across the globe have BI systems either implemented or are in process of implementation.

4. BI systems have seen proven benefits in businesses across the industries like airlines, public administration, health care, FMCG, manufacturing, financial services etc.

Benefits of DW & BI Course

1. The demand for BI experts is increasing at the rate of approximately 25%

per year.

2. This course is meant not only for IT professionals but for industry experts as well since BI is more of a business function now rather than IT function.Business Intelligence

3. Learn from the experts – We have engaged the best brains in the industry with a sea of practical and implementation experience in the field to give you the best available knowledge and share the real life case studies and experiences across different domains to prepare you for the real world.

4. Learn and understand the functionality various tools and technologies for DW & BI.  

Course Contents

Module 1 : Basics of Data & Data Management

Module 2 : Data Warehousing – The Basic Understanding

Module 3 : Data Warehouse : Design & It’s Implementation in Business

Module 4 : Tools & Technologies of DW

Module 5 : Business Intelligence – Origin & Foundation

Module 6 :Designing BI systems for Business Use

Module 7 : Tools & Technologies of BI

Module 8:Project Work

Data science is one of the hottest new professions, yet some say that its demise is not far off. A data scientist crunches huge swathes of data to create meaningful information. However, now with data warehousing taking place at larger than ever levels, and extremely precise algorithms created, the need for a scientist of sorts is fading out. Automation is taking a toll on engineering and scientific jobs and may soon do this to data scientists. The human judgement versus automation debate is in full-swing. Even the term “data science” is coming under debate as some say it isn’t a science but an engineering discipline. Some knowledge workers will get replaced by algorithms but not at the pace a few envisage.


Uploaded Date:14 June 2018

The US regulatory bodies have come in for criticism due to Facebook’s role uncovered in mass data warehousing and foreign interference in federal elections. The position of privacy in the digital age also needs much revision. To close this chasm, some strategies have been illuminated. As a first, tech literacy has to be stepped up among the political and administrative elite in Washington, D.C. Then, stronger policies need to be drafted to take care of third party data, currently held by the likes of Apple, Amazon, Google, Salesforce or Facebook. Investment is needed in new platforms or models which are user-centric and thus take pride in their consent. Currently, users tend to quickly scan through consent forms, while their data gets tracked and sent to large corporates who use it for their digital marketing efforts. Data ethics must be a central tenet to all customer-facing digital companies. In this regard, the European Union’s GDPR (General Data Protection Regulation) has been much more stringent in enforcing the laws.


Uploaded Date:05 June 2018

Amazon is renowned for its lightning quick delivery, even for obscure product requirements. This is not usually because of the delivery system alone, but also due to the concept of demand sensing. Top digital firms such as Amazon are noted for the enormous quantities of data warehousing done, which enables them to predict demand. The obscure product gets delivered so quick because based on the user’s historical data, the company may have simply predicted it being ordered, so had shipped the item long before the actual order was placed. This eases the pressure on the supply chain, reducing market volatility. New data sources are now available that can be tapped to get such vital customer insights. This is even happening in low-volume industries such as wind power equipment or aerospace. The former for example is being worked out by The Swedish-Danish duo of Vattenfall and Orsted leveraging existing neural networks. Several business analytics tools are available to glean this information out of platforms such as social media, connected devices, wearables, geo-location devices and digital personal assistants.


Uploaded Date:16 March 2018

Digital trust has already emerged as one of the key areas of thrust in the so far young year of 2018. The General Data Protection Regulation (GDPR) of the European Union (EU) has already states its aim to better regulate personal data, its protection and the subsequent corporate trust-building. Facebook and Google have similarly voiced their concerns at data protection norms. The former is de-prioritizing content from third party publishers, with the latter making the country origin of content mandatory. Even China’s till-date opaque systems will no longer get a free run at data warehousing on sensitive, personal matters. A study was conducted across forty-two countries, by researchers from the Harvard Business Review to understand the major dimensions on which digital trust is captured. The first of the four captured is Behavior, which in particular talks about the responses by digital players post any friction in the environment or during such digital experiences. The second of these is how users view the attitudes of the players within the digital trust environment. Market research firm Ipsos played a big part in capturing insights among people on data privacy. Then there is the overall Digital Environment that tracks the robustness in implementation of regulator norms towards control mechanisms. And finally, there is the experience of the digital users. While some countries are on the trust-surplus side, majority are on what is the trust-deficit. So, China, Malaysia, Turkey and Saudi Arabia for example are high on trust, Pakistan and Australia are on the other side, with Germany and Japan right towards the middle.


Uploaded Date:03 March 2018

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