5 Things to Consider in Data Analytics Services

The reason, why we love money, is that it gives us purchasing power. Lately, however, headlines like 'data: the new-age digital currency' have been echoing across the enterprise landscape. But data alone is of little value, it is the insights (one of the byproducts of data) that are indicators of its true worth. Data analytics services are helping enterprises make ample use of their data repositories for greater business values. Choosing the right analytics service not only saves enterprises of all the technical headaches but also ensure a complete return of investment.

The Success Pre-requisites

The first thing to do is to clearly draw analytics goals. All enterprises today sit atop a mountain of digital data and making ample use of this data requires that the objective and goals of the analytics process are clearly fixed and defined. Whether it is about faster customer engagements or improving production inefficiencies, data analytics can serve the exact purpose but only if all parameters and constraints are taken into account beforehand.

Here are the things to Consider in Your Data Analytics Service Provider:

1. The Technology Stack:
   Data analytics is a mixed bag of computation and mathematics. Designing and developing an optimal data analytics solution requires expertise across a wide technology domain. The key ones being data engineering, data warehouse, and data visualization. The analytics service provider must have a rich technical workforce with ample experience in handling big data as well as its cleansing.
2. The Consulting: 
   Key practices of any analytics service span from general consulting to workshops for employees. A great analytics service will ensure health checks of your current IT infrastructure as well as smoother onboarding and training of an enterprise's existing workforce.
3. The Onboarding: 
   A big challenge for most enterprises is ensuring that their workforce can easily adapt to the analytic methods, tools and support technologies like cloud, etc. Equally important is the fact that an enterprise must ensure that its key stakeholders are in sync with the key objective and goals.
4. The Security: 
   Data analytics is still a much-debated topic in industry circles. The primary reason being security. Data analytics practices can expose business as well as customer data to hackers and internet bullies. To be on the safer side, enterprises must opt for an analytics service provider which is well known within the industry. The best analytics service provider has SOC and SOC2 certification for maintaining data integrity of their clients.
5. Flexibility and Visualization: 
   Last but not least is flexibility and visualization. Flexibility in the sense that dashboards must be intuitive and rich in data filtering features. In addition to this, the user-interface must make insight generation an easy task. Visualization is a key cog in data analytics. It helps better present ideas and business strategies. Business managers must be able to drive engagement and attention of stakeholders and employees towards strategies that they feel will push towards attaining business goals faster and better. As such visualization backed by insights makes the job easy and effective.

In addition to the above, keeping an eye on internet privacy and data security norms of a particular demographic is an important aspect of analytics. The best analytics services keep track of what and which data can be gathered and cleansed for insights. This is how advanced analytics helping modern businesses. This not only saves companies and businesses from being left red-faced but also contributes significantly to brand loyalty and trust.