5 Biggest Challenges for Data Management

1
5 Biggest Challenges for Data Management

• Contoural Inc

2

• Data is a significant asset for any company. Just
  like humans need quality food to perform well, a
  company needs a consistent supply of quality data
  to function properly. In order to improve a
  companys performance and to meet its goals in a
  timely manner, it is important to have an
  efficient system for data management. The supply
  and quality of data affect a companys
  decision-making ability, impacting business
  productivity.
• According to Michael Cole-Fontayn, Executive VP
  of BNY Mellon, the biggest challenge for any
  company is how data is acquired, saved,
  distributed, and analyzed. To benefit from the
  data optimally, companies need to address a few
  problems. In this article, we have discussed the
  5 biggest challenges for data management.

3
Automation

• Data can be acquired from multiple sources. These
  could be from the internal resource as well as
  external resources. Due to the variety of data
  sources, the gathered data is not different in
  various aspects. Multiple datasets have different
  formats, acceptable ranges, and publication
  periods (granularities). The company faces a
  challenge in handling these datasets because each
  set requires different standards and protocols.
  Another complication arises when the data cannot
  be published when it is required- creating
  undesirable time lag. This calls for the need for
  data automation so that data could be acquired
  and saved efficiently.
• Other than efficiency, automation ensures data
  accuracy and reliability because there are higher
  chances of making mistakes with manual Records
  Management Consultants. Data automation has
  revolutionized the way companies do business.

4
Volume

• The enormous amount of data being created on a
  daily basis has made it quite a challenging task
  to manage data. As the volume of data is
  increasingly growing, it requires more resources
  to monitor and validate the data. In the absence
  of an efficient data management system collecting
  and managing a huge pile of data becomes pretty
  much of a hassle. However, with the right tools,
  this process can be made easier. A good data
  management system sorts out the relevant data and
  manages them for quicker access.

5
Format Changes and Revisions

• Since data is acquired from multiple sources,
  there is a difference in their formats. And data
  managers have another challenge of data
  inconsistency to deal with. With business
  evolution, new aspects are added which tend to
  affect the data format. Or, at times the data
  cannot be made available because it is going
  through the maintenance phase.
• Data vendors need to revise the data because some
  prior entry was incorrect. Data inconsistency
  also occurs when the source data is changed which
  triggers change throughout. You can track these
  changes by going back to the source data however
  doing so frequently can get you blocked by the
  data vendor. And once you have made it to the
  blocked list, it is difficult to refer to the
  same source. Hence, it is important to have an
  efficient data management system, to avoid all
  these consistency issues.

6
Analysis

• Analysis of poor-quality data can be extremely
  challenging and even devastating for analysts,
  managers, and traders within an organization.
  Based on the wrong data, and analysis and
  consequent decisions can be highly destructive
  for the organization because they can steer an
  organization in the wrong direction. Sometimes,
  data experts can identify data errors by
  detecting abnormal patterns however if this task
  is given to a resource, it could be draining and
  frustrating because of its unfeasible nature.
  Those systems that can analyze complex data can
  save a lot of resources for organizations. These
  could be in terms of time, money, stress, and of
  course quality data.

7
Integration

• Because the data is acquired from different
  sources, it is difficult for all the data to meet
  internal system requirements. This data is used
  for assessing and analyzing trade and risk. It is
  used in business intelligence tools, billing and
  invoicing software, and other applications. With
  an efficient system, the data can be utilized and
  integrated for a wide range of applications.

8
Contoural Inc

• Contoural Inc is a reputable and reliable service
  center for data management. Our expert Records
  Management Consultants have provided Data
  Governance Consulting to a wide range of
  companies from various industries. Our team of
  professionals offers the services to collect,
  validate, administer, analyze, automate, and
  prepare reports of your data.

9
THANK YOU

• Address 335 Main St, Los Altos, CA 94022
• Number [phone]
• Email info_at_contoural.com
• Website www.contoural.com