“Right decisions taken at right time guarantees success”
The intent of the statement above was to draw parallels between right decisions, right time and success. The missing element in this trio, which also happens to be their bedrock is, ‘right information’. There is no dearth of data in today’s time and getting information is no big deal. However, drawing meaningful inferences from this ever-increasing data reservoir herald right decisions. No doubt this is a persistent analytics challenge – an inherent quandary of digital transformation. Hence, sieving in Business Intelligence (BI) aimed towards building operational efficiencies into the existing process shall help in galvanising the persistent analytics challenge. This makes the entire decision-making process more agile, more responsive and more intelligent. A sure-shot way to arrive at success.
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Management And Analytics Of Data
Sitting on the mine of petabytes of unstructured data, businesses are exploring ways to sieve out text analytics and sentiment analysis from them. Data hierarchy in correlation to its accessibility by business units or data stratification in terms of experimental data sets or vetted data sets to be used by entire enterprise is still in a nascent stage. This has direct impact on data quality at disposal, effective data curation and tools and technologies to cull out in-depth insights via data discovery. BI comprises dashboard of key performance indicators, which are a form of data. Hence, Data Management is at the core of BI, one which also plays a vital role in Data Analytics strategy. Lack of skilled data analytics is the basic grouse towards robust data management.
Harnessing the unstructured data – Data Analytics holds the key to the future digital world.
The above picture is a sneak peak into the future of Analytics. The important aspect here to note is ‘in real-time’. In ‘real-time’ is the differentiator that yields cutting-edge advantage in ever-changing business environment. On the broader level, we can anticipate following progress.
- Shift towards ‘Story-telling’ – the narrative that emerges out from the data should be
deciphered easily by everyone involved and not dependant on handful of data analysts.
Hence data visualization that presents only data in compact and comprehensible format, the
movement will be towards comprehensible communication which enables in-depth
- Friendly BI tools – evolution of BI tools inherently means evolving dashboards that may not
necessarily require tech-savvy data scientists. It would be navigation friendly, user-friendly
and will bring in collaborative Business Intelligence to achieve the desired outcome.
Besides, there would be flexibility of accessibility which undoubtedly, will bring back the focus
on data security aspect.
- Data Structuring – True there is a mine of data, but of an unstructured data. Data that cannot
be used to any practical purpose if not streamlined. Hence, Data Structuring is a crucial
aspect of BI solutions. Hence, it is imperative that Machine learning emerge as critical
technology enabling structured data formats to help decipher and make processes agile and
- Impact of possible ‘Futures’ – while Descriptive & Predictive Analytics continue to
forecast the understanding of future and advice on possible outcomes, Predictive Analytics
will go a step further in its uptake. Simply because, it gives number of ‘prescriptions’ i.e.
possible outcomes of various decisions. By its sheer concept, it is a complex engine and right
now exists under the purview of only big companies.
Readiness Quotient Is The Question
Corporate decisions-making are increasingly being based on Analytics driven BI, with only 20 percent businesses still waiting on fringes, reports Deloitte. Therein lies the curious case regarding analytical technology – the fact that many of the organisations have only rudimentary analytical technology in place. Then again the report claims that around 96 percent of leaders feel that Analytics has bright future ahead and will become more important within the next three years.
BI & Analytics, no wonder, are the new age technologies and are key to the future. However, the intriguing aspect of any technology adoption is the right skill and positive approach towards change management. These elements themselves are more difficult to embrace than the technology itself. Yet the ‘readiness’ factor for adopting these emerging technologies has received very limited attention.